Engaging and Supporting Problem Solving in Engineering Ethics

July 2009 Journal of Engineering Education 235

Engaging and Supporting Problem Solvingin Engineering Ethics

DAVID H. JONASSEN

School of Information Science and Learning TechnologiesUniversity of Missouri

DEMEI SHEN

University of Missouri

ROSE M. MARRA


YOUNG-HOAN CHO


JENNY L. LO

College of EngineeringVirginia Tech

VINOD K. LOHANI

College of EngineeringVirginia Tech

ABSTRACT

Learning to solve ethical problems is essential to the education of allengineers. Engineering ethics problems are complex and ill struc-tured with multiple perspectives and interpretations to address intheir solution. In two experiments, we examined alternative strate-gies for engaging ethical problem solving. In Experiment 1, stu-dents studied two versions of an online learning environment con-sisting of everyday ethics problems. Students using questionhypertext links to navigate applied more perspectives and canonsand wrote stronger overall solutions to ethics problems than thoseusing embedded hypertext links. In Experiment 2, studentsengaged in a more generative task, evaluating alternative argu-ments for solutions to the cases or generating and supporting theirown solutions. Both groups better supported their solutions andgenerated more counterclaims than control students. These studiesfocused on solving realistic case-based ethics problems as an effec-tive method for addressing ABET’s ethics criteria.

Keywords: argumentation, engineering ethics, problem solving

I. ENGINEERING ETHICS EDUCATION

The job of engineers is very complex. In addition to learningtechnical engineering skills, engineering students must also learn to

work collaboratively with others, communicate effectively, andassume the professional responsibility to recognize and deal withethical issues ( Jonassen, Strobel, and Lee, 2006; Shuman et al.,2004). Because engineers must be prepared to address ethics prob-lems, the ABET, Inc. (formerly know as the Accreditation Boardfor Engineering and Technology, 1997, p. 1) includes in their crite-ria for accrediting engineering programs a requirement that gradu-ates must demonstrate an understanding of professional and ethicalresponsibilities based on economic, environmental, ethical, social,and political constraints. Although ABET criteria may provide anextrinsic rationale for addressing ethics issues in engineering educa-tion, the most compelling rationale is the omnipresent nature ofethical issues in engineering practice.

In this paper, we introduce engineering educators to differentcase-based methods for engaging engineering students in ethicalproblem solving that were implemented in two studies. Rather thanteaching students about ethics, we advocate requiring students tosolve authentic, everyday engineering ethics problems. The ethicalproblems that were solved by individual students in these studiesprovided a sampling of ethics problem solving but did not representthe range of ethical dilemmas that confront engineers. We alsodescribe alternative methods for supporting ethical problem solvingby students, including methods for confronting learners with thecomplexity of ethics problems as well as argumentative methods forhelping students to reconcile those problems.

The rationale for a case-based approach to engineering ethics isthe ill-structured nature of ethics problems. Although they occurduring everyday engineering practice, ethical problems involve con-flicting ethical principles and perspectives that are defined by the dif-ferent roles that engineers play, and they typically have no absoluteright or wrong answers (Fleddermann, 2004). Engineers are mostcommonly employed by corporations, to which they bear an ethicalobligation. On the other hand, engineers also have an ethical respon-sibility to society. Engineers may encounter complicated situations inwhich they need to make choices between investing more money andtime to guarantee the quality of their work for the safety of the publicor to save money for their employers. These situations may initiateconflicts of interest between the employer of engineers and the pub-lic, so engineers may have to decide between the employer’s and thepublic’s best interest. Although engineering professional associationspublish ethical canons to guide behavior, conflicting goals often meanthat canons provide only one perspective on any ethical problem.

If ethics instruction is essential to the preparation of engineers,then the academic community must determine the goals and meth-ods for that preparation. Harris et al. (1996) identified a number ofimportant objectives for ethics instruction:

1. Stimulate the ethical imagination of students2. Help students recognize ethical issues3. Help students analyze key ethical concepts and principles4. Help students deal with ambiguity

5. Encourage students to take ethics seriously6. Increase student sensitivity to ethical issues7. Increase student knowledge of relevant standards8. Improve ethical judgment 9. Increase ethical will-power Newberry (2004) consolidated those objectives into three broader

categories: emotional engagement (the willingness to make ethicaldecisions), intellectual engagement (knowing how to make ethicaldecisions), and particular knowledge (knowing currently acceptedguidelines for ethical practice). Other researchers have stressed theimportance of professional engineering ethical codes, moral reason-ing and humanist readings (e.g., Haws, 2001; Lynch, 1997–98) inethics education. Essentially these approaches describe how engi-neers should be able to recognize ethical problems; reflectively ad-dress those problems by accommodating a variety of perspectives,theories, and ethical codes in their decisions. Haws (2001) arguedthat engineering programs not only push their students to becomeconcerned about the public health and safety of others, but also to(1) help their students to defend their solutions to ethical problems,(2) acquire the ability to evaluate alternative solutions from differentperspectives, and (3) enhance students’ divergent thinking (e.g., un-derstanding situations from other stakeholders’ points of view). Heargued that ethical behavior involves grounding ethical issues in dif-ferent theoretical approaches, considering multiple options withmultiple consequences, and communicating with other stakehold-ers involved. In order to support the research described in thispaper, we attempted to design a learning environment that engagedmost of the goals espoused by Haws (2001). In both studies, engi-neering students were required to accommodate multiple perspec-tives and theories related to everyday ethics problems. In the firststudy, we examined alternative methods for directing students’attention to those perspectives. In the second study, we examinedstudents’ abilities to evaluate and defend alternative solutions toengineering ethics problems.

II. INSTRUCTIONAL METHODS

How is ethics instruction implemented in engineering curricula?Stephan (1999) and Lynch (1997/1998) surveyed methods by whichethics are addressed in engineering curricula. The most common ap-proaches include stand-alone ethics courses within engineering pro-grams, stand-alone ethics courses from outside engineering (e.g.,philosophy departments), integration of ethics across the curriculumin all technical courses, or some combination of these approaches.Within engineering ethics courses, engineering programs use a vari-ety of pedagogical approaches, including studying professional ethi-cal codes, humanist readings to help students gain a more social andhuman understanding from perspectives different from engineers,analyzing ethical cases based on various moral theories, and applyingethical heuristics to ethical problems or decisions (Case, 1998;Haws, 2001). Lloyd, Peter and Van De Poel (2008) argue for a prac-tical understanding of ethical issues in engineering education alongwith the usual theoretical or hypothetical approaches.

Unfortunately, regardless of the methods used, students consis-tently rate the ethics component of an engineering course as theleast interesting, the least useful, and the most trivial (Newberry,2004). Students believe that the study of ethics is irrelevant andtherefore a waste of time, and that their time would better be used

learning more engineering. In order to counter such attitudes, moreengaging methods of instruction are necessary to impress upon en-gineering students the importance of ethics. In order to validatesuch approaches, systematic research is needed; however, little em-pirical research on learning ethical principles has been conducted. Arecent study demonstrated the beneficial effects of metacognitivetraining on mental model construction in ethics problem solving(Brock et al., 2008). This study demonstrated the importance of re-search that focuses on the cognitive requirements of solving ethicalproblems, a belief that informed the design of our current studies.We must better understand how engineers effectively resolve ethicalissues before we can design effective ethical instruction with anycertainty. The current studies provide the beginnings of a series ofstudies on case-based learning in ethics that will hopefully informthe engineering education field.

We began the design of the treatments used in these studies withthe assumption that ethics education must be case-based, employ-ing authentic, everyday problems faced by engineers. Why?Problem-solving instruction is necessarily case-based (Jonassen,2007), so case-based learning is also considered to be the mostappropriate method for engineering ethics education (Harris et al,1996; Kline, 2002). Hipp (2007) proposed a conceptual frameworkto integrate all of the approaches that guide ethical problem solving.His framework prescribes that students identify ethical issues byapplying different ethical theories and professional codes of ethics,identify stakeholders and their perspectives on the issue, generatesolutions according to ethical theories, and make ethical decisionsby referring to the various optional solutions, perspectives and, the-ories. Therefore, for these studies, we designed an online case-based, problem-centered learning environment, Engineer YourEthics (EYE), that integrated ethics scenarios with personal per-spectives on the problem, applications of theories and ethicalcanons, and various tasks for engaging ethical problem solving. Thestudies were conducted serially and were designed to investigatehow to help learners reconcile these perspectives when determininga solution to ethics problems. Before describing the studies, weaddress a number of issues that emerged during the design andimplementation of the EYE learning environment.

III. ISSUES IN ETHICS PROBLEM SOLVING

As we designed the EYE environment and the two studiesreported in this paper, we faced a number of design issues andconstraints that had to be addressed, in the same way the engineer-ing design must accommodate constraints.

A. Decision or Dilemma Traditional models of problem solving, known as phase models,

treat all problems as a process including steps such as identify and de-fine the problem, explore solutions, select and implement a solution,and evaluate the effectiveness of the solution (Bransford and Stein,1984). In our research, we assume that there are different kinds ofproblems (e.g., troubleshooting, decision making, design, dilem-mas), and that each kind of problem requires somewhat differentsolution methods (Jonassen, 2000). Therefore, one of the issues thatwe had to resolve was what kind of problem is an engineering ethicsproblem? In the literature, engineering ethics problems are typicallytreated as either decision-making problems or as dilemmas.

236 Journal of Engineering Education July 2009

Decision-making problems typically require the commitment toand selection of an action from a set of alternative actions. Norma-tive models of decision making stress the expected utility from theselection that is determined by the highest probability of success orthe greatest return from a decision (Kahneman and Tversky, 2000).The most common method for supporting decision making amongnovices is rational choice, in which the decision maker generatesoptions, determines evaluation criteria, evaluates each option interms of the criteria, calculates weights, and selects an alternativebased on weighted criteria. Both approaches have been shown to beunsuccessful because a one-size-fits-all strategy often fails in specificsettings (Klein, 1997). Newer conceptions of decision-making,such as naturalistic decision making (Zsambok and Klein, 1997),examine how experienced people make decisions in contextuallyrich situations.

For many, ethical problems represent dilemmas. Rhetorically, adilemma is an argument between two equally undesirable, opposingpositions. Doubt and uncertainty cloud dilemmas because neitheroption is practically acceptable, that is, neither is immediately prefer-able. There are different kinds of dilemmas, including social dilem-mas and ethical dilemmas. Social dilemmas counter pose personalinterests against societal interests, each party representing a positionthat is untenable to the other. In dilemmas, neither resolution willbe acceptable by the majority of people. Ethical dilemmas presentmutually exclusive alternatives that imply a moral dimension.

Not surprisingly, there are differences of opinion on the natureof engineering ethical problems. Kligyte et al. (2008) emphasize theimportance of ethical decision-making skills in engineering whereasLozano et al. (2006) and Magun-Jackson (2004) argue that ethicalproblem solving involves the resolution of moral dilemmas with thefinal goal of attaining a post-conventional moral reasoning, accord-ing to Kohlberg’s (1981) theory of moral reasoning.

Although there are many moral implications in ethical problemsolving, for purposes of these studies, we assumed that engineeringethics problems are decision-making problems. Engineering ethicsproblems are psychological because engineers must reconcile alter-native solutions with vaguely defined or unclear goals and con-straints in order to decide on a course of action. Although ethicalissues frequently involve dilemmas, we assume that engineersattempt to make rational decisions that involve various factors, suchas economic goals, environmental factors, public safety, and others(Sindelar et al., 2003). These multiple dimensions are indicative ofthe varied relationships that engineers must maintain with theiremployers, the public, society, and themselves, each involving dif-ferent responsibilities and loyalties, most of which are resolvable,unlike many dilemmas. Finally, dilemmas frequently involve moraldimensions, which are problematical to research.

B. Authenticity of ProblemsContemporary learning theories stress the importance of em-

bedding instruction in authentic, everyday problems (Jonassen,2004). However, there have emerged two broad conceptions ofauthenticity, preauthentication and emergent authenticity. Preau-thentication refers to analyzing activity systems and attempting tosimulate an authentic problem in a learning environment. Preau-thentication is what Barab and Duffy (2000) refer to as a practicefield, in which students can practice learning how to function insome field, such as engineering ethics. Fields of practice (Barab andDuffy, 2000) refer to embedding students in an authentic setting,

allowing them to learn a skill by engaging in the activities germaneto that field (Barab, Squire, and Dueber, 2000; Nicaise, Gibney,and Crane, 2000; Radinsky et al., 2001). Fields of practice possessattributes of apprenticeships. The authenticity emerges from thepractice in an authentic setting. The type of authenticity used inthese studies was preauthentication, because these studies involvedinstruction in regular educational settings, which occurs withinconstraints such as class size that preclude engagement in authenticpractices.

Having selected simulated problems as the focus of EYE, thenext decision related to authenticity was the nature of the ethicsproblems that were provided for students to solve. An analysis oftextbooks on engineering ethics (e.g., Fledderman, 2008; Harris,Pritchard, and Rabins, 2005; Lynch, 2000) shows a proclivity forproviding catastrophic case studies for students to analyze, such asthe Challenger and Columbia explosions, the crash landing of theDC-10 in Iowa, the Ford Pinto, or the collapse of the pedestrianbridge in the Kansas City Hyatt. Although each of those casesinvolved serious ethical issues, it is most unlikely that engineeringgraduates will ever be involved in such cases. More likely, graduateswill face more prosaic ethical issues that are embedded withineveryday practice. Therefore, we included everyday cases such ascode enforcement, accepting gifts from suppliers, and cutting cor-ners on design testing in EYE—cases that practicing engineers aremore likely to encounter.

IV. EXPERIMENT 1: SUPPORTING ENGINEERING ETHICS

PROBLEM SOLVING VIA DIFFERING LINK TYPES

The primary purpose of this first study was to explore how toget students to more thoroughly investigate different perspectives,theories, and canons when solving engineering ethics problems.The instructional design model that best addresses the underlyingcomplexity of engineering ethics problems is Cognitive FlexibilityTheory (CFT) (Spiro et al., 1988, 1987; Spiro and Jehng, 1990).Spiro claimed that traditional instruction oversimplifies the com-plexity and irregularity of domain knowledge, relies mainly on a sin-gle representation or theory, and focuses too much on abstract con-text-independent representations. Rather than reducing ambiguityand simplifying problems to be solved, CFT stresses the conceptualinterrelatedness of ideas being studied. Instruction that is basedupon CFT should reflect the complexity that normally faces practi-tioners, rather than treating practical, professional problems as sim-ple, linear sequences of decisions. In order to do that, CFT pre-scribes that learners examine multiple (not single) cases frommultiple perspectives, themes, domains, or disciplinary approaches.CFT conveys the interconnectedness and irregularity of knowledgein random access, non-linear hypertexts, known as cognitive flexi-bility hypertexts (CFH) (Spiro and Jehng, 1990). Based on the as-sumption that prerequisite concepts must be learned prior to ad-vanced concepts, Spiro claimed that CFT is more appropriate foradvanced knowledge acquisition than introductory learning. Thatclaim is consistently questioned by the assumptions, methods, andresearch in problem-based learning, which these studies employed.Despite his claims, most of the empirical research (reported next)was conducted in introductory learning situations.

CFT employs a metaphor of crisscrossing the knowledge land-scape, a metaphor that Spiro borrowed from Wittgenstein (1953)


indicating “a nonlinear and multidimensional traversal of complexsubject matter, returning to the same place in the conceptual land-scape on different occasions, coming from different directions”(Spiro et al., 1992). When students crisscross cases, they examinethem from different perspectives. Crisscrossing highlights the mul-tifaceted features of each case and can help establish various connec-tions between cases, thus helping learners construct a flexibleknowledge that can be adapted to solving new problems. Criss-crossing is essential for complete understanding of the problem.

A few quality empirical studies on CFH environments havebeen conducted in various learning domains. Most of these studieshave examined to what degree students do examine and considerdifferent perspectives. Harvey (1999) investigated the effectivenessof different tasks (judging whether sexual harassment had occurredvs. generating a workplace policy on harassment) on crisscrossingand knowledge transfer. Because the task types were cognitivelysimilar, no differences in crisscrossing or knowledge transferoccurred. However, the attitude change of the policy group washigher and more positive than the judging group.

When comparing a computer based drill that emphasized fac-tual knowledge and theme identification with a thematic crisscross-ing treatment that stressed the interrelatedness of case-specificknowledge components, Jacobson and Spiro (1995) found that thedrill group recalled more factual knowledge, while the experimentalgroup had significantly higher scores on problem-solving essaysthat measured knowledge transfer. In a follow-up study using thesame environment, Jacobson et al. (1996) compared three differentconditions, including guided crisscrossing, learner-directed criss-crossing, and free exploration of the hypertext. In the guided treat-ment, students were guided through different perspectives andthemes in the hypertext, a strategy that modeled good crisscrossingperformance. There was no modeling in the learner-directed treat-ment. Similar to the previous study, the free exploration group andthe learner-directed groups outperformed the guided group onfactual knowledge acquisition. Jang (2000) found that high schoolstudents using a cognitive flexibility hypertext on Korean historyperformed better on comparison, analysis, and synthesis tasksthan students who studied a hierarchical hypertext or a traditionaltextbook.

The research on CFT is far from definitive, but it generallyshows that crisscrossing helps learners to interconnect concepts andexamine case problems from different perspectives and themes.However, crisscrossing cases is an unfamiliar method of studying,so students need to be assisted in order to crisscross effectively(Spiro et al., 1992). In complex environments with random accessto instruction such as CFHs, learners may not understand the struc-ture that guides their traversals (Spiro et al., 1996) and thereforemay not crisscross as much as anticipated. So, in this first experi-ment, we examined the effects of different kinds of links for encour-aging crisscrossing and comprehension of case problems.

Because solving engineering ethics problems requires the con-sideration of multiple perspectives and themes, the purpose of thisstudy was to investigate how crisscrossing perspectives, cases, andthemes can be fostered. Crisscrossing is normally afforded by high-lighted links to other perspectives, themes, or cases that are embed-ded in the text. Clicking on a link displays information related tothe selected perspective, case, or theme. This study sought to inves-tigate how learners could be encouraged to follow these links toinvestigate the ethics cases more fully if those embedded links were

presented as questions to be answered. In this first study, weexamined whether changing embedded links from declarative to aquestion format might lead to more crisscrossing because questionsattract attention (Ge and Land, 2003) and promote thinking thathelps solve the problem (Clasen and Bonk, 1990; Tinsley, 1973).Various studies have shown that questions can elicit metacognitionin Web-based learning environments (Davis and Linn, 2000) andcan foster ill-structured problem solving processes (Ge and Land,2003, 2004).

Embedding questions in learning environments may also modelquestion-asking performance. Question asking is “a stage in the prob-lem solving process” (Ashmore, Frazer, and Casey, 1979, p. 426).Learners’ abilities to generate questions may also be used as an alter-native method for assessing problem-solving performance in casestudies (Dori and Herscovitz, 1999). Because question asking isseen as an important skill in problem solving, we examined theeffects of link type on question generation in the present study.Specifically, our research questions included:

• Will participants who use EYE with question links accessmore information (crisscross) more than students who usethe CFH with embedded links?

• Will solutions to ethical problems constructed by partici-pants who use the CFH environment with question linksdiffer from the performance of those who use the CFH withembedded links?

• Will participants who use the CFH environment with ques-tion links generate more questions or higher-order questionsthan participants who use the CFH with embedded links?

V. METHODS

1) Context: All participants in this study were enrolled in a 2-credit hour course, Engineering Exploration, offered at a largesoutheastern university. The course was required for first-year engi-neering students. The course includes “foundation material in prob-lem definition, solution, and presentation; design, including hands-on realization working in teams; modeling and visual representationof abstract and physical objects; scientific computation; algorithmdevelopment, computer implementation and application; docu-mentation; ethics; professionalism” (Lo, Lohani, and Mullin, 2006,p. 2). The present study was conducted during the three-week uniton engineering ethics.

2) Participants: The final sample for the study included 116participants, 95 (81.9 percent) male and 21 (18.1 percent) female.One hundred five participants were Caucasian (90.5 percent) and 9(5.8 percent) were Asian- and Pacific-American. Two (1.8 percent)participants were not United States citizens. The majority ofstudents, 112 (96.6 percent), were first-year students while only 4(3.4 percent) were second-year students.

3) Materials: The EYE CFH consisted of two teaching cases(cases 1 and 2), one practice case (case 3), and one assessment case(case 4). Each case represents an everyday ethical problem that en-gineers might encounter. Case 1 involved a manufacturing engineeraccepting golf matches and betting on them with a supplier. Case 2focuses on a building engineer who is required by the city councilchairman to grandfather some buildings under construction inorder to be able to hire more building inspectors to keep up withwork. Case 3 is a whistle-blowing case involving polluted effluents


from a company into a local lake. Case 4 involves a decision to bringsoftware up to new standards at increased costs to the company thatmay result in job losses.

For the teaching cases and the practice case (Cases 1, 2 and 3),there are four categories of links on the right hand side of the screen(see Figure 1), which provide alternative interpretations of the case.The links enable the students to examine each problem from theperspective of each character in the case, from different theoreticalapproaches, or from ethical canons promoted by the National Soci-ety of Professional Engineers, and evaluate the better solution toethical problems. Following the links helped students apply a prob-lem solving process described by Hipp (2007) to the case.

Cases 1 and 2 were teaching cases, as they demonstrated theproblem-solving process as well as a completely worked out caseanalyses and case solutions. Clicking on each link displayed on theright side of Figures 1 and 2 (perspectives, theories, and canons) pre-sents interpretations of the problem from different personal perspec-tives, different theoretical perspectives, and different ethical canons.Figure 2 illustrates an interpretation of the case from the utilitariantheory approach. It is important to note that each perspective de-scribed an interpretation of the problem from that perspective. Forexample, in Figure 2, following a brief definition of the utilitariantheory, the students read how the problem would be interpreted byeach of the primary persons in the case from a utilitarian perspective.


Figure 1. Problem presentation for Cases 1 and 2 for both experiments.


That is, each interpretation was an application of that perspective,theory, or canon, not just a definition of each. For Cases 1 and 2,alternative solutions to the problem were presented, and each wasjustified by reiterating the personal perspective, theories, andcanons that support that solution (Figure 3).

For the two teaching cases (Cases 1 and 2), two alternative treat-ments were developed. The first treatment included embeddedlinks that enabled students to navigate through the environment(see bottom of screen in Figure 4). In the alternative treatment,these embedded links were replaced by questions (see Figure 5).Question links were used in this treatment to promote crisscrossingand deeper levels of thinking (Dori and Herscovitz, 1999). The twoversions of the environment were exactly the same with the excep-tion of the link types. Both of the environments were designed tofoster in-category crisscrossing (comparing perspectives, theoreticalapproaches, solutions, etc) and cross-category crisscrossing (connect-ing perspectives to theoretical approaches, approaches to solutions,etc). There was a one-to-one mapping between the links presented

in the embedded-links and question-links versions of the environ-ments. To design the questions used in the question links versionwe used Bloom’s Taxonomy to vary the levels of questions, assum-ing that higher order thinking would be stimulated by higher levelsof questions (Wisher and Graesser, 2005).

Case 3 was the practice case. Rather than providing case analysisbased on alternative perspective, theories, canons, and solutions tothe problem, text boxes were provided for students to enter theirown answers to the practice case. Expert answers were providedwhen students completed and submitted their answers.

Case 4 was a delayed assessment case that was used to assessethical problem-solving transfer. For the assessment, studentswere asked to generate a list of questions that would be necessaryto resolve the case, and then they wrote an essay to answer thosequestions.

4) Procedure: The course was organized around main lecture sec-tions accompanied by smaller workshop sessions. Students attend-ed one 50 minute lecture and one 50 minute workshop session per

Figure 2. Presentation of perspectives, theories, and canons for both experiments.

week. All participants in this study were enrolled in the same lecturesection, so all participants in the two groups had the same classroomlecture from the same instructor. Participants were divided into twogroups by intact workshops and used one of the two different ver-sions of the CFH learning environment. Students in two work-shops were assigned to Group One and used the environment withquestion links, and students in the other three workshops were as-signed to Group Two, using the environment with embedded links.

During the three weeks assigned to ethics, participants studiedEYE and completed the activities in a self-paced manner outside ofclass. These activities replaced the normal lecture and video onengineering ethics. During the first class lecture for the ethics unit,each student was given an instructional page which contained aURL of one of the two CFH environments, written instructions onhow to sign up and log on to EYE, and what they should do tocomplete the learning tasks in the environments. The URL directedstudents to the Web page where they registered. Following regis-tration, each participant received an e-mail containing his or heruser name and password that enabled that student to log on to theenvironment.

Participants were required to complete the teaching cases andthe practice case in the first two weeks and the assessment case dur-ing the final week. The assessment case was not made available on-line until the end of the second week, and the prior cases were madeunavailable during the time period when the assessment case was

being completed. Participants’ scores on the assessment essay werepart of their final grade.

5) Data Analysis: In this study, we applied a between-grouppost-test only design to investigate the influence of different typesof links in two CFH learning environments on problem-solvingperformance in engineering ethics. The question generation andcase analysis essays were collected online. For the assessment case,students were asked to (a) generate a list of questions (5–10) in orderto resolve the case, and (b) write an essay to answer the questions theygenerated and solve the case. The analysis of questions generated bystudents used criteria established by Dori and Herscovitz (1998): ori-entation, relation to case study, and complexity of the question. Fourvariables were used to assess the question generation performance:

• Question total count (total number of questions generated byeach participant)

• Relevant question count (number of questions judged to be re-lated to the problem in the CFH environments—do questionsrelate to perspective, theories, canons, solutions, or decisions)

• Level of questions (level of question classified by Bloom’sTaxonomy: knowledge and comprehension classified aslower-order and application, comprehension, analysis, andsynthesis classified as higher-order)

• Relevant higher-order question count (number of questionsclassified as higher-order and also related to perspectives,theories, canons, solutions, or decisions


Figure 3. Alternative solution and justification for Cases 1 and 2 for Experiment 1 only.


In the assessment case, students were supposed to identify theperspectives of characters, apply various ethical theories, apply ethi-cal canons, generate alternative solutions, and make decisions. Aholistic rubric (see Table 1) based on these components was used toevaluate their problem solving performance on the case analysisessay. The maximum score was 20 with 0–4 points possible for eachcategory of the problem solving processes.

Two raters (both Ph.D. students) scored the assessment essaysand questions generated by students. The inter-rater reliability was82.5 percent for the essays, and 89.0 percent for the questions, re-spectively. When there was disagreement, the raters resolved theirdifferences, so that the final reliability rating was 100 percent.

To compare how the two groups used the CFH environment,participants’ clicks were tracked. We measured four variables, in-cluding overall frequency of links used (i.e., clicked) by participants,revisiting frequency (crisscrossing), number of unique links visited,and frequency of special links used (question links and embeddedlinks). The first variable included the total counts of all of the linkseach individual visited in the learning environment. The secondvariable was crisscrossing, the number of times that participantsrevisited links. The third variable was the number of unique linksvisited by participants. This variable included the number of differ-ent links each participant accessed in the learning environment.

The fourth variable was the frequency of using question links in thequestion link group and the frequency of clicking embedded links inthe embedded link group.

In order to compare the effects of the treatments, a one-waymultivariate analysis of variance (MANOVA) was conducted. Theindependent variable was the treatment, and the dependent vari-ables were the students’ performance on question generation andcase analysis essays. To compare the effects of the treatments onusage, clicks of links were summed. Multiple sets of t-tests wereconducted to discover differences on frequency of clicks on links.

VI. RESULTS

The primary purpose of this study was to examine differences inperformance in solving engineering ethics problems between twogroups of participants using different kinds of links in CFH envi-ronments. We gathered three kinds of data: participants’ perfor-mance on the essay, a question generation task, and an analysis ofthe participants’ use of the environments. To acquire a basic under-standing of the relationship of the main variables, bivariate correla-tion analysis was applied to performance scores (total essay score,total generated question count, and total number of clicks on all

Figure 4. Embedded links at bottom for Experiment 1 only.

links). In the question link group, participants’ use of the Web site,as measured by the total number of links they used, correlatedsignificantly with their performance on the problem solving essays(r � 0.41, p � 0.05). The more frequently students used the Website, as measured by the frequency of clicks in the CFH environ-ment, the better their scores were on the problem solving essay. Asimilar relationship was found between Web site use and essayscores (r � 0.37, p � 0.05) for the embedded link group. In addi-tion, the correlation between the number of generated questionsand the problem solving essay score was also significant: r � 0.43,p � 0.01 for the question link group and r � 0.30, p � 0.01 for theembedded link group. The more questions the participants gener-ated and tried to answer when solving the ethical case, the betteressays they wrote.

Problem solving performance was assessed using two measures:case analysis essays and question generation. Two MANOVAswere performed on scores of case analysis essays and question gen-eration as dependent variables and two groups as independent vari-

ables. The assumptions for MANOVA were checked and a prelim-inary analysis was conducted. Scores on the case analysis essay (seeTable 2) ranged from 2 to 20 with a mean of 14.64 and a standarddeviation of 5.40. For the question link group, the range of totalcase analysis essay scores was 4 to 20, with a mean of 15.67. Therange for the five separate criteria was 0 to 4. The mean scoresranged from 2.84 to 3.37. For the embedded link group, the highesttotal case analysis essay score was 20 (the same as for the questionlink group); the lowest was 2, with a mean case analysis essay scoreof 13.26. For the five individual criteria, the mean score rangedfrom 2.18 to 3.33. The range of scores for the five criteria was thesame as for the question link group, 0 to 4.

A one-way MANOVA showed a significant multivariate effectfor group on the set of dependent variables, F (5, 110) � 2.32, p �0.05, �2 � 0.10). Univariate analyses indicated significant effects ofgroup on three of the six dependent variables: identifying perspec-tives of characters, applying ethical canons, and overall total score.Univariate analyses represented a small effect of group on the three


Figure 5. Question links at bottom for Experiment 1.


dependent variables (�2 ranging from 0.05 to .06). The results alsoindicated the marginal influence of group on applying ethicaltheories ( p � 0.09).

Question generation performance was assessed in four ways: thetotal number of questions generated by each participant; the numberof questions that addressed multiple perspectives, ethical theories,ethical canons, multiple solutions, or decisions); the total number oflower-order (knowledge and comprehension on Bloom’s Taxonomy)generated based; and the number of higher-order questions (appli-cation, analysis, synthesis, and evaluation on Bloom’s Taxonomy)related to ethical problem solving.

The two groups of participants generated 714 questions in totalwith a mean of 6.15. The question link group generated 406 ques-tions (M � 6.06) and the embedded link group generated 308 (M �6.29). However, the question link group generated more questionsrelevant to problem solving processes (324) than did the embeddedlink group (215), with each individual in the question link group gen-erating 4.73 relevant questions and 4.39 in the embedded link group.Bloom’s Taxonomy was used to classify the level of students’ think-

ing as reflected in their questions. Participants in the question linkgroup generated 1.18 lower-order questions and 4.84 higher-orderquestions on average, whereas the embedded link participants gen-erated 1.18 lower-order questions and 5.19 higher-order questionson average. Each question link participant generated 3.87 higher-order questions targeting problem solving, whereas each embeddedlink participant generated 3.53 of this type of question. A one-wayMANOVA indicated no significant multivariate effect of link typeon the set of dependent variables, F (10, 105) � 0.85, p � 0.05.

Finally, we measured the frequency of clicks on links as an indi-cator of crisscrossing. Although these data provide no evidence ofcognitive processing that occurred during page visits, they doprovide evidence of how broadly students investigated the cases.Participants in both groups used the main links in Cases 1 and 2fairly frequently. In Case 1, participants in the question link groupused the 62 special question links 157 (M � 2.34) times, whereasparticipants in the embedded link group used the 62 special embed-ded links 56 (M � 1.14) times. Similarly, in Case 2, the questionlink participants clicked on the 58 special links 100 (M � 1.49)

Table 1. Holistic rubric for evaluating case analysis essays.

times, while the embedded link participants clicked on their speciallinks 28 (M � 0.57) times. In addition, there were more clicks onthe links in Case 3 than in Cases 1 and 2 in both groups.

To determine if the groups’ use of the three cases differed signif-icantly, the total clicks on all links in each case were summed andthree independent sample t-tests were performed. Results indicatedno significant difference in the number of clicks on links in Case 1,Case 2, and Case 3 between the two groups, t(114) � 0.94, p �0.05, t(114) � �0.34, p � 0.05, t(113.97) � 1.85, p � 0.05, re-spectively. In the question link group, participants’ overall frequencyof visiting all links ranged from 20 to 342 visits, with a mean totalfrequency of 125.10. In this group, the revisiting frequency rangedfrom 5 to 285 visits, with a mean revisiting frequency of 81.94.Participants visited from 11 to 72 unique pages, with a mean of34.13. The frequency of using question links ranged from 0 to 33,with an average of 3.85. In the embedded link group, the total fre-quency of clicks ranged from 6 to 284 visits, with a mean total visit-ing frequency of 118.31. The revisiting frequency ranged from 2 to213 visits, with a mean revisiting frequency of 72.47. Participants inthis group visited 4 to 53 unique links, with a mean of 35.10. Thefrequency of using embedded links ranged from 0 to 10, with anaverage of 1.71.

Four sets of independent sample t-tests were performed todetect any differences between the question link and embeddedlink groups on the four variables. The results showed no significantdifference between the two groups on the first three variables,t(114) � 0.58, t(114) � 0.95, t(114) � �0.49, ps � 0.05. Resultsindicated that, for special links, question links were more frequentlyused than embedded links, t(88.64) � 2.58, p � 0.05.

VII. DISCUSSION

Although there are many different instructional approaches forteaching engineering ethics, many ignore the complexity of ethicalissues (Hipp, 2007). CFT is an instructional model for supportingthe acquisition and construction of advanced knowledge and prob-lem solving (Jacobson and Spiro, 1995; Jang, 2000). This studyattempted to apply the characteristics of CFT to foster ethical prob-lem solving. Crisscrossing conceptual landscapes is the fundamentalmechanism of CFT. Through crisscrossing, complex subjectsbecome more “graspable” than when explored in a single linear con-text (Spiro and Jehng, 1990, p. 170). However, there is no guaran-

tee that learners in cognitive flexibility hypertexts will actuallycrisscross.

Our hypothesis was that crisscrossing can be fostered by usingquestions as links, which are navigational components that anchorhypertext and guide users to relevant parts of a hypertext. Resultsindicate the form of the link had no significant effect on the amountof crisscrossing. That is, both groups accessed similar numbers oflinks while studying the ethics cases. In terms of navigational per-formance, there were no significant differences in the frequency ofclicks on all links in the CFH environment, the frequency of revisit-ing links (crisscrossing), and the number of unique links visited byindividuals. Nor were there differences in the frequency of using alllinks, the frequency of revisiting links (crisscrossing), or the numberof unique links visited.

Although the form of link did not affect navigation, it appears tohave had an effect on students’ analysis of the ethics problems. Intheir essay solutions to the transfer ethics case, the participants whoused the CFH environment with question links identified moreperspectives, applied ethical canons more frequently, and wrotestronger overall solutions to the transfer ethics problem than thosewho used the CFH with embedded links. These findings are con-sistent with previous research that indicates question prompts wereeffective in facilitating ill-structured problem solving (Ge andLand, 2003; Ge, Chen, and Davis, 2005). Researchers have arguedthat questions and questioning are beneficial to learning in severalways. Questions may provoke thinking and attract learners’ attention(Ge and Land, 2003). Questioning may help individuals concen-trate on learning materials and monitoring problem solvingprocesses (King, 1994), and higher-order questions help improvecritical thinking (Renaud and Murray, 2007).

The questions did not affect all kinds of problem-solving perfor-mance. That is, there were no differences in students’ applicationsof ethical theories or generation of multiple solutions while makinga decision. Applying ethical theories such as the Utilitarian ap-proach, the Rights and Duty approach, and the Virtue approachwas likely an unfamiliar and demanding task for these inexperi-enced students. Applying theories to case analysis requires decom-posing the case according to intangible ethical theories to findmoral dimensions, a more complicated task than identifying char-acters’ perspectives and applying ethical canons. Applying theoriesand canons to generate solutions, rather than memorizing them,requires higher levels of cognitive behavior, including synthesis (ofall the information to generate solutions) and evaluation (of the


Table 2. Participants’ performances on the problem solving essay in Experiment 1.


solutions by comparing consequences and alignment with the the-ories, canons, and perspectives). It appears that link type was notsufficient for overcoming the complexity of the analysis required tosolve ethics problems.

Additionally, performance on question generation was similarbetween groups. The two groups had comparable scores on thetotal number of questions generated, the number of relevant ques-tions, the number of lower-order questions or higher-order ques-tions based on Bloom’s Taxonomy, and the number of higher-orderquestions associated with the five categories of ethical problem solv-ing in engineering (identifying character’s perspectives, applyingethical theories, applying canons, generating multiple solutions, andmaking a decision). Based on these findings, it seems that questionlinks did not help participants generate more or better questions.Many instructional approaches used to train students to generatequestions are not effective (Rosenshine, Meister, and Chapman,1996). It appears that the question links were not adequate modelsfor generating better questions. Question generation is an activeprocess requiring a higher level of cognitive strategies (Garcia andPearson, 1990) than reading questions (King, 1994; Rosenshine,Meister, and Chapman, 1996). Therefore, reading questions alonemay not be sufficient to help students begin to generate questions.

Another important perspective for interpreting the results is thatquestion generation is not an assessment method commonly used inhigher education, although it has been proposed as an alternativeassessment method in science (Dori and Herscovitz, 1999). Stu-dents can generally ask questions in the classroom, but questions arenot usually required or assessed. Thus students in this study mayhave found the idea of generating questions somewhat foreign andmay not have exerted sufficient effort to performing effectively onthis new task.

This first experiment showed that analyzing information in arandom access hypertext in order to construct meaningful solutionsto engineering ethics problems was a difficult task for these stu-dents. Although question links did support students’ solutions to alimited degree, they were insufficient for affecting students’ overallethical investigations. Nor did they provide an adequate model forgenerating student questions. In a similar study using randomaccess hypertexts, Jonassen and Wang (1993) found that the natureand structure of links had little effect on students comprehension ofinformation contained in the hypertext, but the nature of the taskhad a much more significant effect. Therefore, in Experiment 2, weexamined the effects of a task that would necessitate crisscrossingand analysis more deeply.

VIII. EXPERIMENT 2: ARGUING TO LEARN TO SOLVE

ETHICS PROBLEMS

In the first experiment, we showed that merely providing alter-native perspectives, theories, and canons was only partially effectivein stimulating students to apply those theories. Although partici-pants in the question link group provided more perspectives andcanons than participants in the embedded link group, other assess-ments of higher order thinking (question generation) showed nodifference between the treatments. For engineering students to betruly fluent in addressing engineering ethics problems, they need tobe able to demonstrate a deeper understanding of the problems andthe solutions they are proposing. That is, merely examining alterna-

tive perspectives may not be sufficient for getting students to pay at-tention to or apply them. Given these results, we designed the nextstudy to help students be able to more deeply justify their solutionsthrough argumentation.

The most important factor in learning is the nature of the task inwhich learners are engaged. That is, the nature of the task driveslearning. If we want students to develop more meaningful justifica-tions for their solution to ethics problems, we must engage them in amore meaningful and generative task. Among the most powerfulmethods for assessing the ability to solve ill-structured problems, likeethics problems, is the production of coherent arguments to justifysolutions and actions (Jonassen, 2004). Cho and Jonassen (2002)found that scaffolding argumentation during group problem-solvingactivities increased the generation of coherent arguments and re-sulted in more problem-solving actions during collaborative groupdiscussions. Argumentation was more important when solving ill-structured problems than well-structured problems because of theimportance of generating and supporting alternative solutions.

Kuhn (1991) identified five essential skills of argumentation:generating causal theories to support claims, offering evidence tosupport theories, generating alternative theories, generating coun-terarguments, and rebutting alternative theories. Although theskills of argumentation have been clearly identified, the ability ofstudents to generate or evaluate arguments is questionable. Accord-ing to Reznitskya et al. (2001), most American students do notunderstand argumentative discourse. They experience difficultywriting persuasive essays, comprehending written arguments, dif-ferentiating between theory and evidence, generating genuineevidence, alternative theories, counterarguments or rebuttals (Kuhn,1991; Means and Voss, 1996). They are unlikely to construct two-sided arguments or distinguish evidence from explanation in sup-port of a claim (Kuhn, 1991; Voss and Means, 1991; Kuhn, Shawand Felton, 1997). Therefore, intellectual skill development pro-vides another rationale for engaging students in argumentation. Inthis study, we examined the role of argumentation in supportingengineering ethics problem solving. Rather than asking students toanalyze a case and synthesize a solution merely by accessing infor-mation in a random access hypertext, this study examined theeffects of alternative forms of argumentation on students’ solutionsto engineering ethics problems.

The most common weakness in argumentation is the lack ofcounter-argumentation, which requires that students recognizealternative claims, that those claims require different reasons to sup-port them, and how to rebut those alternative claims and reasons.Research has consistently validated the tendency of students toavoid two-sided arguments (Felton and Kuhn, 2001; Kuhn, 1991;Kuhn, Shaw, and Felton, 1997; Voss and Means, 1991). In order tocounteract that tendency, Nussbaum and his colleagues have exam-ined a variety of strategies, including the refutation strategy, thesynthesizing strategy, and the weighing strategy (Nussbaum andSchraw, 2007). In the refutation strategy, students learn to recog-nize alternative solutions and to rebut those arguments. The refuta-tion strategy is an implicitly adversarial strategy. In the synthesizingstrategy, students try to develop a compromise position that com-bines merits of both sides (“Is there a compromise or creative solu-tion?”). In the weighing strategy, students must learn to evaluatealternative arguments and support the stronger argument based onthe weight of evidence on that side of the issue (“Which side isstronger and why?”). When writing opinion essays, students need to

integrate both argument and counterarguments in order to developa conclusion (Nussbaum and Schraw, 2007).

Argumentation can be divided into the skill of analyzing argu-mentative texts and the skill of composing one’s own argument,which are under-developed in college students (Marttunen, 1994).Analyzing argumentative texts is a form of dialectical argumenta-tion while composing one’s own is a form of rhetorical (also knownas persuasive or constructive) argumentation. There are two aspectsof argumentative text—its generation and its evaluation (Voss,Wiley, and Sandak, 1999). Effective argumentation requires notonly considering counterarguments but also evaluating, weighing,and combining arguments and counterarguments into support for afinal position (Nussbaum and Schraw, 2007). In this study wemodified the EYE environment to require students to either con-struct arguments or to evaluate alternative solutions. Our goal wasto compare the structure of arguments generated by students whoconstruct their own solution to a series of engineering ethics prob-lems with those of students who were asked to evaluate alternativesolutions to those problems. The primary research questions thatguided Experiment 2 were:

• Will argumentation improve the quality of students’ solu-tions to engineering ethics problems?

• Will solutions to ethical problems (immediate transfer anddelayed transfer) constructed by participants who use theCFH environment requiring students to construct argu-ments during training differ from the performance of thoserequired to evaluate alternative solutions?

IX. METHOD

1) Participants: One hundred and forty-three first-year studentsenrolled in three separate workshop sections of a required first-yearengineering education course (the same course used in Experiment 1in a different semester) at a southeastern university served as partici-pants in this study. Participation was solicited, and permission foruse of data was obtained via verbal consent. Eighty-three percent ofthe students were male and 17 percent female. Seventy-threepercent of the participants were Caucasian. The remaining studentswere Asian American (14 percent), Hispanic (4 percent), andAfrican-American (5 percent). Most of the participants (89 percent)were first year students (7 percent sophomore, 3 percent junior) en-rolled in the College of Engineering, planning to complete an un-dergraduate degree in an engineering major.

2) Design: This study utilized a quasi-experimental post-test-delayed post-test design. Participants were enrolled in one of threeworkshop sections of a first year engineering education course.Sections were randomly assigned to the three treatment options.Because the content was deemed entirely novel to first year stu-dents, no pre-test was performed. There were 48 participants in theevaluate arguments group, 46 in the construct arguments group,and 49 in the control (summarize the case) group.

3) Materials: Participants in three workshop sections workedindividually through a modified version of the EYE environment toread, analyze, and write arguments in support of a solution to threeengineering ethics cases. EYE was initially designed as a cognitiveflexibility hypertext (Spiro and Jehng, 1991) for Experiment 1. Themodified environment consisted of three of the ethics cases used inExperiment 1.

For this study, three versions of the EYE environment weredeveloped: an evaluate arguments treatment, a construct argu-ments treatment, and a control (summarize) treatment. The onlydifference between the treatments was in the nature of the task.The structure and content of the cases were the same as those inExperiment 1; however the task was varied for each of the threetreatment groups in Experiment 2. Participants in the evaluatetreatment were assigned the task of evaluating two alternative solu-tions while interacting with the case evidence. For the training case(Case 1), each participant in the evaluate treatment answered a seriesof questions related to the golfing case:

• Which solution is better, solution 1 or solution 2?• Whose perspective(s) support(s) your selection?• Which theoretical approach(es) support(s) your selection?• Which Ethical Codes support your selection?• How might someone supporting the other solution disagree

with your preferred solution?In the construct arguments treatment, participants were asked

to construct their own solution to Case 1. Participants answered aseries of questions related to the golfing case:

• What should you, as the engineer, do? What is your solutionto this ethical problem?

• Whose perspective(s) support(s) this solution?• Which theoretical approach(es) support(s) your solution?• Which Ethical Codes support your solution?• What might someone else do? What alternative solution

might someone recommend?• What reasons would someone provide to support this

solution?In the control treatment, the structure and content of the envi-

ronment was identical to the evaluate arguments and construct ar-guments treatments except for the task. In Case 1, participants wereasked to “summarize different perspectives, theoretical approachesand ethical canons” in Case1.

Case 2 represented an immediate transfer case. It told a storyabout an engineer who was the building director and had to makea decision between getting additional resources if he “grandfa-thered” certain properties in order to encourage business develop-ment and strictly and fairly enforcing building codes. The per-spectives included the engineer’s and the city council chairman’s,and the theoretical approaches and canons were the same as inCase 1. In Case 2, the question prompts were removed, and stu-dents in both treatments were required to describe their solutionto a new ethics problem and to provide reasons why that was thebest solution. Participants were asked to “Explain why you believethat the solution you propose is the best one.” This problem wasintended to assess immediate recall of the effects of the differentquestion prompts used to focus the task in Case 1. In Case 2 (im-mediate transfer task), the instructions were identical for each ofthe treatment groups.

Case 3, the delayed transfer case, was completed during a 30-minute session one week following the initial treatment. It recountsa story of a software engineer who is challenged by a new set of stan-dards for environmental monitoring software at nuclear powerplants. Accommodating the new standards would be time-consum-ing and costly. In Case 3, no perspectives, theories or canons werepresented. Participants were instructed to write an essay answering:“What will you recommend regarding the additional software test-ing of the new system? Justify your recommendation as best you


can. Provide as many reasons as you can to justify [support] yourposition and try to provide evidence. Think of as many reasons asyou can on both sides of the issue when developing your answer.Justify your recommendation with perspectives, theories, and/orcanons.” The purposes of this transfer case were to assess both thestructure of the argument and participants’ recall of and use ofperspectives, theories, and canons.

4) Procedures: All activities were completed during normallyscheduled workshop times. Students were required to bring theirlaptop computers to every class, so they could access EYE andcomplete the experiment. After being notified of the consentprocess, a researcher delivered a statement concerning the impor-tance of ethical behavior in the practice of engineering and indicat-ed that the cases the participants would solve were exemplary ofethical problems that they may face as engineers. Next, theresearcher presented instructions on how to use the online envi-ronment (EYE). Students then worked individually for up to onehour completing the activities. After completing each case, partici-pants saved their responses, which were encoded into a MySQLdatabase. During the follow-up session one week later, a researcherrepeated the instructions for how to use the environment to com-plete Case 3. Students used up to one half hour to complete andsave their responses.

5) Coding: To assess participants’ performance in Case 1, tworesearchers graded the quality of responses to questions on a 3-point scale (0 � not containing any answer, 1 � containing ananswer without sufficient elaboration, 2 � containing an answerwith sufficient elaboration) and then added the scores. The inter-rater agreement was initially 87 percent and 100 percent after dis-cussion. Participants’ argumentative essays in Cases 2 and 3 wereanalyzed using the coding scheme described in Table 1. The codeswere designed to assess whether participants adequately completedthe activities called for in the environment. That is, how frequentlydid the participants cite perspectives, theories, or canons in supportof the claims they selected or generated. More importantly, did theparticipants consider counterclaims, and did they support themwith case evidence, including perspectives, theories, or canons?This scheme is similar to several argumentation coding schemes(Nussbaum and Kardash, 2005; Nussbaum and Schraw, 2007)that identify claims, counterclaims, supporting reasons, and rebut-tals, except that our scheme identified specific types of supportingreasons.

All responses to all cases received a frequency score for eachdependent variable. For example, the score for SupportingReasons–Theories reflected the frequency with which each partici-pant referred to theories to support their clams or counterclaims.Students’ responses to each case were initially parsed by oneresearcher, who identified idea units within each response. Therewere a total of 1,569 idea units generated among the three treat-ments (574 for the evaluate treatment, 517 for the construct treat-ment, and 478 for the summarize treatment). Then two individu-als coded all of the responses (masked to treatment). Out of the1,569 idea units, inter-rater agreement prior to any reconciliationwas 70 percent. After discussing differences, agreement was 100percent.

In addition to frequency codes, each participants total set ofresponses for each case was evaluated for overall quality on a 6-pointscale modifying a rubric reported by Ferretti, MacArthur, and

Dowdy (2000) that is listed in Table 3. This rubric emphasized sup-port for the argument, whether counterclaims were identified andrebutted, and overall clarity and organization. Each complete caseresponse was rated by two raters, who agreed 64 percent of the timeprior to reconciliation (100 percent).

X. RESULTS

Descriptive statistics for Cases 2 and 3 are presented in Table 4.A one-way Analysis of Variance (ANOVA) indicated that totalidea units of Case 2, the immediate transfer task, were significantlydifferent among three groups, F (2, 140) � 5.75, p � 0.004, �2 �0.08. A post hoc test (Tukey HSD) showed that participants in theevaluate group created significantly more idea units than partici-pants in the control (summarize) group, M � 5.79 vs. 4.41, p �0.003, but there was no significant difference between the constructand the control group, M � 5.09 vs. 4.41, p � 0.23. In Case 3, thedelayed transfer task, total idea units were marginally differentamong three groups, F (2, 140) � 2.79, p � 0.065, �2 � 0.04.

Multivariate multiple regression analyses were carried out withtreatments and Case 1 performance as independent variables andargument components (i.e., the solution, perspective supportingsolution, theory supporting solution, canon supporting solution,and counterclaim) as dependent variables. Treatments were dummycoded and standardized scores (z-scores) were used to measureCase 1 performance because the scales of three Case 1 treatmenttasks were different.

For Case 2, the result of the multivariate multiple regressionindicated that the evaluate group was significantly different fromthe control group in argument components, Wilks’ � � 0.91, F (5,135) � 2.59, p � 0.028, whereas the construct group was not sig-nificantly different from the control group, Wilks’ � � 0.97, F (5,135) � 0.85, p � 0.518. The Case 1 performance marginally in-fluenced argument components in Case 2, Wilks’ � � 0.93, F (5,135) � 1.91, p � 0.096. Follow-up univariate multiple regressionanalyses showed that the evaluate treatment was more effective thanthe control treatment in the theory supporting solution, B � 0.38,SE � 0.16, p � 0.019, and the counterclaim, B � 0.44, SE � 0.17,p � 0.01. Case 1 performance significantly influenced the theorysupporting solution, B � 0.02, SE � 0.01, p � 0.037, and the canonsupporting solution, B � 0.02, SE � 0.01, p � 0.029.

Differently from Case 2, the evaluate group was not significantlydifferent from the control group in Case 3, Wilks’ � � .94, F (5,135) � 1.81, p � 0.116, but the effect of Case 1 performance on argu-ment components was significant, Wilks’ � � 0.81, F (5, 135) � 6.48,p � 0.001. The construct group was not significantly different fromthe control group in Case 3, Wilks’ � � 0.95, F (5, 135) � 1.54,p � 0.181. Follow-up univariate multiple regression analysesshowed that Case 1 performance significantly influenced thetheories supporting solution, B � 0.04, SE � 0.01, p � 0.001, andthe counterclaims, B � 0.03, SE � 0.01, p � 0.004.

Next, participants’ argumentative essays for Cases 2 and 3 wereassessed for the overall quality of the essays. In Case 2 holisticscores, a one-way Analysis of Variance (ANOVA) indicated thatthere were significant differences among three groups, F (2, 140) �6.38, p � 0.002, �2 � 0.08. A post hoc test (Tukey HSD) showedthat the evaluate group produced higher quality essays than the



Table 3. Holistic rubric for assessing Cases 2 and 3 performances in Experiment 2.

Table 4. Argument component and holistic scores of three treatment groups.

control group (M � 2.63 vs. 2.04, p � 0.003) and the constructgroup also wrote higher quality essays than the control group (M �2.5 vs. 2.04, p � 0.025). However, there was no significant differ-ence between the evaluate and the construct group (p � 0.755).Additionally, there was no significant difference among threegroups in Case 3 holistic scores, F(2, 140) � 1.18, p � 0.31, �2 �0.02, indicating that the effects of the argumentation treatments didnot transfer to the delayed transfer task.

XI. DISCUSSION

In this study, we altered the nature of the task from the firstexperiment, asking participants to construct or evaluate argumentsto support their solutions to ethics problems. We hypothesizedthat constructing or evaluating arguments would provide a moregenerative purpose for considering the perspectives, theories, andcanons that were provided to interpret the ethics problems. Priorresearch on cognitive flexibility hypertexts, including our own,shows that crisscrossing cases and using multiple sources of evi-dence is not a naturally occurring process among students, sorequiring learners to use those sources of evidence to support argu-ments would enhance their understanding of ethical issues. Addi-tionally, we sought to evaluate whether a rhetorical or a dialecticalform of argumentation would produce better solution justifications(van Eemeren and Grootendorst, 1992; van Eemeren, Grootendorst,and Henkemans, 1996), specifically the functional roles of eachargumentative move in resolving disagreements. We producedalternative instructional treatments that required students to con-struct their own solutions and justifications (rhetorical or persua-sive form of argumentation) or evaluate alternative solutions andjustifications (a dialectical form of argumentation). Previous researchfound that when students justify their own claims, they producepoorer arguments with fewer counterarguments (Nussbaum andKardash, 2005) than when they consider alternative claims andjustifications.

The results from Experiment 2 supported our belief that argu-mentation would prove to be a more meaningful and engaging taskfor resolving engineering ethics cases than merely navigating throughperspectives, as in Experiment 1. Both treatments resulted in strongerarguments relative to the control group; however, we found no sig-nificant advantage for constructing and justifying personal solutionsover evaluating alternative solutions. In the immediate transfer case,participants in the experimental conditions generated more theoriesto support their solutions, more counterclaims, and more theories tosupport counterclaims than the control group. Those effects fadedsomewhat in the delayed transfer, a week later. It appears that theexperimental treatments may have interfered with the delayedtransfer task. However, we showed that scaffolding argumentationin training cases can enhance the quality of students’ arguments.

Consistent with other research (Felton and Kuhn, 2001; Kuhn,1991; Kuhn, Shaw, and Felton, 1997; Stein and Bernass, 1999;Voss and Means, 1991), students in this study failed to adequatelyconsider and support counterclaims, providing more elaborate sup-port for their own solutions. Because counterarguments are a hall-mark of argumentations skills, future studies will focus on methodsfor eliciting stronger support for counterarguments. In the nextstudy, we will ask participants to write as many reasons as possiblewhy others might disagree with a given solution and compare the

effects of self-generated counterarguments with counterargumentsgenerated by peers.

Argumentation is an essential skill in solving ill-structured prob-lems. Experiment 2 is the first in a series of studies to examinemethods for improving the quality of students’ arguments in sup-port of engineering ethics problems. More research is needed toexamine alternative methods for doing so. In subsequent studies, wewill investigate alternative methods for fostering counter argumen-tation among these students.

XII. CONCLUSION

Haws (2001) claimed that engineering programs should helptheir students to consider public health and safety of clients andothers by defending their solutions to ethical problems, evaluatingalternative solutions from different perspectives, and enhancing stu-dents’ divergent thinking (e.g., understanding situations from otherstakeholders’ points of view). He argued that ethical behavior in-volves grounding ethical issues in different theoretical approaches,considering multiple options with multiple consequences, andcommunicating with other stakeholders involved. We attempted toapply those assumptions in the design of a Web-based learningenvironment, Engineer Your Ethics. The EYE environment pre-sented realistic, everyday ethical problems for students to solve andconveyed the complexity and ambiguity of those cases by presentingmultiple solutions, multiple perspectives on those solutions, multi-ple theories for interpreting those solutions, and a set of ethicalcanons specific to engineers. Students were required to considereach of those perspectives, theories, and canons when formulatingand supporting their solutions to the cases.

We conducted two studies using the EYE environment. In thefirst study, we found that students’ solutions to ethics cases werepartially enhanced by providing questions to guide their investiga-tions of the ethics problems. However, the question-link treatmentdid not result in consistently better performance on case analysis orquestion generation than the embedded-links treatment. Wehypothesized that the nature of the task in experiment one was notsufficiently powerful to produce the desired results. Further, merelypaying attention to structural cues in hypertext (link types) is muchmore strongly affected by the some tasks than others (Jonassen andWang, 1993).

Therefore, in Experiment 2, we investigated the effects of stu-dent construction or evaluation of arguments on their solutions toengineering ethics problems. Defending their solutions, evaluatingalternative solutions from different perspectives, and enhancingstudents’ divergent thinking (Haws, 2001) imply a specific form ofargumentation. In Experiment 2, we showed that scaffolding ar-gumentation in training cases does enhance the quality of student’sarguments, and that student argumentation is a more generativetask, capable of engendering deeper thinking about the ethicsproblems.

Our purpose in conducting these studies was to conduct an ini-tial examination of how to engage engineering students in ethicalproblem solving. We do not presume that these are definitive stud-ies in engineering ethics; however, they do describe nascent at-tempts to conduct empirical research in a discipline that has engen-dered very little empirical research. Rather than teachingengineering students about ethics, we believe that it is important to


actually require students to apply ethical theories in order to recon-cile ethical dilemmas in engineering. Also, we assume that thestrategies used in these studies could be employed in face-to-faceclassroom teaching as well.

We recognize some significant limitations to these studies, so theresults may not be generalizable to other populations. First, the extentof the treatment was relatively short (1 1⁄2 hours). Because of a veryfull course curriculum we had limited access to the students, so theyhad time to solve only a few ethics cases. A more complete under-standing of ethical issues would require solving more problems ad-dressing a wider range of ethical problems, such as social justice. TheEYE environment provides a model for designing case-based learn-ing environments for engaging students in ethical problem solving.

Second, these studies involved mostly first-year students wholack the background knowledge that may make ethical problemsmore realistic and meaningful. This course represented the only re-quired exposure to ethics in the engineering curriculum, and thesample population was one of convenience. Generalizing thesefindings would require running similar experiments with differentlevels of students and, if possible, practitioners.

Third, in order to maintain some experimental control, thesestudies involved a limited number of interventions, including ques-tioning strategies in the first study and argumentation strategies.Nor did our studies involve any face-to-face component, however,it is likely that a blended form of instruction, integrating both on-line and classroom based activities and discussions, would providemore powerful lessons in ethics. Another powerful form of assess-ment or problem transfer might include student-generated ethicscases ( Jonassen, 2006) where groups of students generate their ownethics cases, perspectives, and issues and perhaps guide class discus-sion of those cases. These activities would require a much greaterallocation of time in the course. There are clearly many other typesof interventions that would reasonably support ethical problemsolving. We are conducting additional studies examining differentmethods for enhancing the role of argumentation in ethical prob-lem solving. Analysis of the data from those studies should provideadditional insights into how to integrate argumentation into ethicalproblem solving.

Fourth, because of limited access to the students in the samplepopulation, we were unable to conduct qualitative, follow-up re-search activities that are necessary to better understand students’reasoning while studying the learning environment. Future researchmay involve think-aloud protocols or abstracted replays in order togain insights into student reasoning.

Finally, because engineering problem solving is usually a collab-orative activity ( Jonassen, Stobel, and Lee, 2006), ethical problemstypically involve collaborative activities. The focus of these studieswas on individual interpretation of ethics cases. Subsequent studiesshould examine collaborative interpretations of and resolutions toethics problems.

In order fulfill ABET’s requirement that engineering graduatesbe prepared to address ethical problems, we believe that ethicalproblem-solving activities should be embedded within every engi-neering course. In these studies, first year students attempted to rec-oncile everyday engineering ethics problems. Because they have notyet constructed an identity as an engineer, it is likely that they foundthe activity somewhat less relevant than seniors or practicing engi-neers might. As students progress through the engineering curricu-lum, assuming more engineering roles, the importance of such

ethical problem solving should seem more relevant. If a single two-hour exposure to ethical problems becomes their only exposure toethics in the engineering curriculum, it is safe to predict that gradu-ates will be unprepared to meaningfully address engineering ethicsproblems. Because of the importance of ethics to engineering prac-tice, we believe that more research is needed to validate the most ef-fective methods for engaging and supporting ethics learning. Inthese two studies, we provide empirical support for the use of ques-tions and arguments for supporting learning in case-based environ-ments. So much more research is needed. Even so, these studiespoint to the possible positive impact of the use of meaningful ques-tions and argumentation in engineering ethics education—and wenote that these instructional strategies can be implemented effec-tively in non-technology-based environments. However, the po-tential impact of the use of technology is also a significant result.

Finally, these studies support the use of online approaches toengaging engineering students in ethics problem solving. Onlineproblem solving can serve large numbers of students simultaneous-ly. Additionally, students’ responses can be automatically collectedand assessed, providing immediate feedback to course instructors.

ACKNOWLEDGMENT

This material is based upon work supported by the NationalScience Foundation under Grant Nos. 0618459 and 0618541. Anyopinions, findings, and conclusions or recommendations expressedin this material are those of the authors and do not necessarilyreflect the views of the National Science Foundation.

REFERENCES

Ashmore, A.D., M.J. Frazer, and R.J. Casey. 1979. Problem solving

and problem solving networks in chemistry. Journal of Chemical Education

56 (6) 377–79.

Barab, S.A., and T.M. Duffy. 2000. From practice fields to communi-

ties of practice. In Theoretical foundations of learning environments, eds. D.H.

Jonassen and S.M. Land, pp. 25–55. Mahwah, NJ: Lawrence Erlbaum

Associates.

Barab, S.A., K.D. Squire, and W. Dueber. 2000. A co-evolutionary

model for supporting the emergence of authenticity. Educational Technolo-

gy: Research and Development 48 (2): 37–62.

Bloom, B.S., D.R. Krathwohl, and B.B. Masia. 1956. Taxonomy of

educational objectives; the classification of educational goals. New York:

Longman Group.

Bransford, J.D., and B.S. Stein. 1984. The IDEAL problem solver.

New York: W.H. Freeman.

Brock, M., A. Vert, V. Kligyte, E. Waples, S. Sevier, and M. Mumford.

2008. Mental models: An alternative evaluation of a sensemaking approach

to ethics instruction. Science and Engineering Ethics 14 (3): 449–72.

Case, E.D. 1998. Integrating professional ethics into technical courses

in material science. In Proceedings of the American Society on Engineering

Education Annual Conference. Seattle, WA.

Cho, K.L., and D.H. Jonassen. 2003. The effects of argumentation

scaffolds on argumentation and problem solving. Educational Technology:

Research and Development 50 (3): 5–22.

Clasen, D.R., and C. Bonk. 1990. Teachers tackle thinking. Madison,

WI: Madison Extension Program.


Davis, E.A., and M. Linn. 2000. Scaffolding students’ knowledge in-

tegration: Prompts for reflection in KIE. International Journal of Science

Education 22 (8): 819–37.

Dori, Y.J., and O. Herscovitz. 1999. Question-posing ability as an al-

ternative evaluation method: Analyses of an environmental case study.

Journal of Research in Science Teaching 36 (4): 411–30.

van Eemeren, F.H., an R. Grootendorst. 1992. Argumentation, com-

munication, and fallacies: A pragma-dialectical perspective. Hillsdale, NJ:

Erlbaum.

van Eemeren, F.H., R. Grootendorst, and F.S. Henkemans. 1996.

Fundamentals of argumentation theory: A handbook of historical backgrounds

and contemporary developments. Mahwah, NJ: Erlbaum.

Felton, M., and D. Kuhn. 2001. The development of argumentative

discourse skill. Discourse Processes 32 (2&3): 135–53.

Ferretti, R.P., C.A. MacArthur, and N.S. Dowdy. 2000. The effects

of an elaborated goal on the persuasive writing of students with learning

disabilities and their normally achieving peers. Journal of Educational

Psychology 92 (4): 694–702.

Fleddermann, C.B. 2008. Engineering ethics, 3rd Ed. Upper Saddle

River, NJ: Pearson Prentice Hall.

Garcia, G.E., and P.D. Pearson. 1990. Modeling reading instruction to

maximize its effectiveness for all students (Tech. Rep. No. 489). Champaign,

IL: University of Illinois, Center for the Study of Reading.

Ge, X., and S.M. Land. 2003. Scaffolding students’ problem-solving

processes in an ill-structured task using question prompts and peer interac-

tions. Educational Technology Research and Development 51 (1): 21–38.

Ge, X., and S.M. Land. 2004. A conceptual framework for scaffolding

ill-structured problem solving using question prompts and peer interac-

tions. Educational Technology Research and Development 52 (2): 5–22.

Ge, X., C. Chen, and K. Davis. 2005. Scaffolding novice instructional

designers’ problem-solving processes using question prompts in a Web-

based learning environment. Journal of Educational Computing Research

33 (2): 219–48.

Harris, C.E. Jr., M. Davis, M.S. Pritchard, and M.J. Rabins. 1996. En-

gineering ethics: What? Why? How? and When? Journal of Engineering

Education 85 (2): 93–96.

Harris, C.E., M.S. Pritchard, and M.J. Rabins. 2005. Engineering

ethics: Concepts and cases, 2rd Ed. Singapore: Thomsen.

Harvey, D.H. 1999. Investigations of cognitive flexibility hypertexts: From

theory to application. Unpublished Doctoral Dissertation, the Pennsylvania

State University

Haws, D.R. 2001. Ethics instruction in engineering education: A

(mini) meta-analysis. Journal of Engineering Education 90 (2): 223–29.

Hipp, C. 2007. An integrative approach to teaching engineering

ethics.In Proceedings of American Society for Engineering Education Annual

Conference. Honolulu, Hawaii.

Jacobson, M.J., and R.D. Spiro. 1995. Hypertext learning environ-

ments, cognitive flexibility, and the transfer of complex knowledge: An

empirical investigation. Journal of Educational Computing Research 12 (4):

301–33.

Jacobson, M.J., C. Maouri, P. Mishra, and C. Kolar. 1996. Learning

with hypertext learning environments: Theory, design, and research

Source. Journal of Educational Multimedia and Hypermedia 5 (3/4): 239–81.

Jang, S. 2000. Effects of cognitive flexibility theory-based instruction

on Korean high school history teaching. Distance Education 21 (1): 136–61.

Jonassen, D.H. 2000. Toward a design theory of problem solving.

Educational Technology: Research and Development 48 (4): 63–85.

Jonassen, D.H. 2004. Learning to solve problems: An instructional design

guide. San Francisco, CA: Pfeiffer/Jossey-Bass.

Jonassen, D.H. 2006. Typology of case-based learning: The content,

form, and function of cases. Educational Technology 6 (4): 11–15.

Jonassen, D.H. 2007. What makes scientific problems difficult? In

Learning to solve complex, scientific problems, ed. D.H. Jonassen, 3–23.

Mahwah, NJ: Lawrence Erlbaum Associates.

Jonassen, D.H., and S. Wang. 1993. Acquiring structural knowledge

from semantically structured hypertext. Journal of Computer-based Instruc-

tion 20 (1): 1–8.

Jonassen, D.H., J. Strobel, and C.B. Lee. 2006. Everyday problem

solving in engineering: Lessons for engineering educators. Journal of Engi-

neering Education 95 (2): 1–14.

Kahnemann, D., and A. Tversky. 2000. Choice, values, and frames.

Cambridge, UK: Cambridge University Press.

King, A. 1994. Guiding knowledge construction in the classroom:

Effects of teaching children how to question and how to explain. Ameri-

can Educational Research Journal 31 (2): 338–68.

Klein, G. 1997. An overview of naturalistic decision making applica-

tions. In Naturalistic decision making, eds. C.E. Zsambok and G. Klein,

49–59. Mahwah, NJ: Lawrence Erlbaum Associates.

Kline, R.R. 2002. Using history and sociology to teach engineering

ethics. IEEE Technology and Society Magazine 20 (4).

Kligyte, V., R. Marcy, E. Waples, S. Sevier, E. Godfrey, M. Mumford,

and D. Hougen. 2008. Application of a sensemaking approach to ethics

training in the physical sciences and engineering. Science and Engineering

Ethics 14 (2): 251–78.

Kohlberg, L. 1981. Essays in moral development. New York: Harper.

Kuhn, D. 1991. The skills of argument. Cambridge, UK: Cambridge

University Press.

Kuhn, D., V. Shaw, and M. Felton. 1997. Effects of dyadic interac-

tion on argumentative reasoning. Cognition and Instruction 15 (3):

287–315.

Lloyd, Peter, and I. Van De Poel. 2008. Designing games to teach

ethics. Science & Engineering Ethics 14 (3): 433–447

Lo, J., V.K. Lohani, and J. Mullin. 2006. Student presentations on

contemporary engineering ethics issues in an introductory freshman

engineering course. In Proceedings of 2006 ASEE Annual Conference and

Exposition. Chicago, IL.

Lozano, J.F., G. Palau-Salvador, V. Gozálvez, and A. Boni. 2006.

The use of moral dilemmas for teaching agricultural engineers. Science

and Engineering Ethics 12 (2): 327–34.

Lynch, W.T. 1997/1998. Teaching engineering ethics in the United

States. IEEE Technology and Society Magazine 16 (4): 27–36.

Lynch , W.T. 2000. Engineering practice and engineering ethics. Sci-

ence, Technology & Human Values 25 (2): 195–225.

Magun-Jackson, S. 2004. A psychological Model that Integrates

Ethics in Engineering Education. Science and Engineering Ethics 10 (2):

219–24

Marttunen, M. 1994. Assessing argumentation skills among Finnish

university students. Learning and Instruction 4 (2): 175–91.

Means, M.L., and J.F. Voss. 1996. Who reasons well? Two studies of

informal reasoning among children of different grade, ability, and knowl-

edge levels. Cognition and Instruction 14 (2): 139–78.

National Academy of Engineering. Online Ethics Center, http://

www.onlineethics.org (last accessed April 2009).

Newberry, B. 2004. The dilemma of ethics in engineering education.

Science and Engineering Ethics 10 (2): 343–51.

Nicaise, M., T. Gibney, and M. Crane. 2000. Toward an understand-

ing of authentic learning: Student perceptions of an authentic classroom.

Journal of Science Education and Technology 9 (1): 79–94.


Nussbaum, E.M., and C.M. Kardash. 2005. The effects of goal in-

structions and text on the generation of counterarguments during writing.

Journal of Educational Psychology 97 (2): 157–69.

Nussbaum, E.M., and G. Schraw. 2007. Promoting argument-

counterargument integration in students writing. Journal of Experimental

Education 76 (1): 59–92.

Olson, G.M., S.A. Duffy, and R.L. Mack. 1985. Question-asking as a

component of text comprehension. In The psychology of questions, eds. A.C.

Graesser and J.B. Black. Hillsdale, NJ: Erlbaum.

Radinsky, J., L. Buillion, E.M. Lento, and L. Gomez. 2001. Mutual

partnership benefit: A curricular design for authenticity. Journal of Cur-

riculum Studies 33 (4): 405–30.

Renaud, R.D., and H.G. Murray. 2007. The validity of higher-order

questions as a process indicator of educational quality. Research in Higher

Education 48 (3): 319–51.

Reznitskya, A., R.C. Anderson, B. McNurlin, K. Nguyen-Jahiel, A.

Archodidou, and S.Y. Kim. 2001. Influence of oral discussion on written

argumentation. Discourse Processes 32 (2&3): 155–75.

Rosenshine, B., C. Meister, and S. Chapman. 1996. Teaching stu-

dents to generate questions: A review of the intervention studies. Review

of Educational Research 66 (2): 181–221.

Shuman, L.J., M.F. Sindelar, M. Besterfield-Sacre, H. Wolfe, R.L.

Pinkus, R. L. Miller, B.M. Olds, and C. Mitcham. 2004. Can our students

recognize and resolve ethical dilemmas? In Proceedings of the American Soci-

ety of Engineering Education Annual Conference and Exposition. Salt Lake

City, UT.

Sindelar, M., L. Shuman, M. Besterfield-Sacre, R. Miller, C.

Mitcham, B. Olds, R. Pinkus, and H. Wolfe. 2003. Assessing engineering

students’ abilities to resolve ethical dilemmas. In Proceedings of the Frontiers

in Education Conference. Bolder, CO.

Spiro, R.J., W. Vispoel, J. Schmitz, A. Samarapungavan, and A.

Boerger. 1987. Knowledge acquisition for application: Cognitive flexibili-

ty and transfer in complex content domains. In Executive control processes,

ed. B.C. Britton. Hillsdale, NJ: Lawrence Erlbaum Associates.

Spiro, R.J., R.L. Coulson, P.J. Feltovich, and D.K. Anderson. 1988.

Cognitive flexibility theory: Advanced knowledge acquisition in ill-structured

domains. Tech Report No. 441. Champaign, IL: University of Illinois,

Center for the Study of Reading.

Spiro, R.J., and J.C. Jehng. 1990. Cognitive flexibility and hypertext:

Theory and technology for the non-linear and multi-dimensional traversal

of complex subject matter. In Cognition, education, and multimedia: Explo-

rations in high technology, eds. D. Nix and R.J. Spiro. Hillsdale, NJ:

Lawrence Erlbaum.

Spiro, R.J., R.P. Feltovich, M.J. Jacobson, and R.L. Coulson. 1992.

Cognitive flexibility, constructivism, and hypertext: Random access in-

struction for advanced knowledge acquisition in ill-structured domains. In

Constructivism and the technology of instruction: A conversation, eds. T.M.

Duffy and D.H. Jonassen, 57–76. Hillsdale, NJ: Erlbaum.

Stein, N.L., and R. Bernas. 1999. The early emergence of argumentative

knowledge and skill. In Foundations of argumentative text processing, eds. J.

Andriessen and P. Corrier, 97–116. Amsterdam: Amsterdam University

Press.

Stephan, Karl D. 1999. A survey of ethics-related instruction in

U.S. engineering programs. Journal of Engineering Education 88 (4):

459–64.

Tinsley, D.C. 1973. Use of questions. Educational Leadership 30 (8):

710–13.

Voss, J.F., and M.L. Means. 1991. Learning to reason via instruction in

argumentation. Learning and Instruction 1 (4): 337–50.

Voss. J,F., J. Wiley, and R. Sandak. 1999. Reasoning in the construction of

argumentative texts. In Foundations of argumentative text processing, eds. J. An-

driessen and P. Coirier, 29–41. Amsterdam: University of Amsterdam Press.

Wisher, R.A., and A.C. Graesser. 2005. Question asking in advanced

distributed learning environments. In Toward a science of distributed learning

and training, eds. S.M. Fiore and E. Salas. Washington, DC: American

Psychological Association.

Wittgenstein, L. 1953. Philosophical investigations. Oxford: Blackwell

Zsambok, C.E., and G. Klein. 1997. Naturalistic decision making.

Mahwah, NJ: Lawrence Erlbaum Associates.

AUTHORS’ BIOGRAPHIES

Dr. David Jonassen is Distinguished Professor of Education atthe University of Missouri where he teaches in the areas of Learn-ing Technologies and Educational Psychology. He has published30 books and numerous articles, papers, and reports on text design,task analysis, instructional design, computer-based learning, hyper-media, constructivist learning, cognitive tools, and problem solving.His current research focuses on the cognitive processes engaged byproblem solving and models and methods for supporting thoseprocesses, including causal reasoning, analogical reasoning andargumentation during learning.

Address: University of Missouri, School of Infomration Scienceand Learning Technologies, 221C Townsend Hall, Columbia,MO 65211; e-mail: [email protected].

Dr. Demei Shen is a Postdoctoral Fellow at the University ofMissouri-Columbia. She received her doctoral degree in informa-tion science and learning technologies from the same institution in2008. Her research interest includes factors that influence onlinelearning and teaching, social computing, and engineering educa-tion. Her current research focuses on online learning self-efficacybeliefs and factors that influence learning achievement of studentsin engineering classroom.

Address: University of Missouri-Columbia, 303 Townsend Hall,Columbia, MO 65211; e-mail: [email protected].

Dr. Rose M. Marra is an associate professor in the School ofInformation Science and Learning Technologies at the Universityof Missouri. She holds a Ph.D. in Educational Leadership andInnovation, a MS in computer science and worked as a softwareengineer for Bell Laboratories. She is currently co-director of theNSF-funded Assessing Women and Men in Engineering (AWE)and Assessing Women in Student Environments (AWISE) pro-jects, and Co-PI of the National Girls Collaborative Project. Herresearch interests include STEM education with an emphasis onengineering, gender equity in STEM, the epistemological develop-ment of college students, and promoting meaningful learning inweb-based environments.

Address: University of Missouri, 303 Townsend Hall, Columbia,MO 65211; e-mail: [email protected].

Young Hoan Cho is a Ph.D. student in the School of Informa-tion Science and Learning Technologies at the University ofMissouri. His current research interest is learning from examples inill-structured domains: engineering ethics, writing, mathematicsteacher education, and instructional design.


Address: of Missouri, 303 Townsend Hall, Columbia, MO65211; e-mail: [email protected].

Dr. Jenny Lo is an Advanced Instructor in the Department ofEngineering Education at Virginia Tech. She received her doc-torate in chemical engineering from Carnegie Mellon Universityin 1999. Her current research interests include curriculum devel-opment, engineering ethics and academic advising for first-yearengineering students.

Address: Virginia Tech, Department of Engineering Educa-tion, 323 Randolph Hall, Blacksburg VA 24061; e-mail: [email protected].

Dr. Vinod K Lohani is an associate professor in the EngineeringEducation Department and an adjunct faculty in the Civil and Envi-ronmental Engineering at Virginia Tech. He received a Ph.D. in civilengineering from Virginia Tech in 1995. His research interests are inthe areas of knowledge modeling, water and energy sustainability, en-gineering learning modules for freshmen, and international collabo-ration. He leads a major curriculum reform project (2004–09), fund-ed under the department-level reform program of the NSF, atVirginia Tech. A spiral curriculum approach is adopted to reformu-late engineering curriculum in bioprocess engineering in this project.

Address: Virginia Tech, Department of Engineering Education,660 McBryde Hall, Blacksburg VA 24061; e-mail: [email protected].


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Engaging and Supporting Problem Solving in Engineering Ethics