Teaching Programming by Emphasizing Self-direction-ACM-ToCE

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Teaching Programming by Emphasizing Self-Direction: How DidStudents React to the Active Role Required of Them?

VILLE ISOMOTTONEN and VILLE TIRRONEN, University of Jyvaskyla

Lecturing is known to be a controversial form of teaching. With massed classrooms, in particular, it tends toconstrain the active participation of students. One of the remedies applied to programming education is touse technology that can vitalize interaction in the classroom, while another is to base teaching increasinglyon programming activities. In this article, we present the first results of an exploratory study, in which weteach programming without lectures, exams, or grades, by heavily emphasizing programming activity, and,in a pedagogical sense, student self-direction. This article investigates how students reacted to the activerole required of them and what issues emerged in this setting where self-direction was required. The resultsindicate three issues that should be taken into account when designing a student-driven course: the challengeof supporting students’ theoretical synthesis of the topics to be learned, the individual’s opportunities forself-direction in a group work setting, and mismatch between individual learning processes and academiccourse scheduling.

Categories and Subject Descriptors: K.3.2 [Computers and Education]: Computers and InformationScience Education—Computer Science Education

General Terms: Human Factors, Theory

Additional Key Words and Phrases: Self-direction, programming education

ACM Reference Format:Isomottonen, V. and Tirronen, V. 2013. Teaching programming by emphasizing self-direction: How didstudents react to the active role required of them? ACM Trans. Comput. Educ. 13, 2, Article 6 (June 2013),21 pages.DOI: http://dx.doi.org/10.1145/2483710.2483711

1. INTRODUCTION

Many studies on programming education have concentrated on paradigm, language,and tools. Recently, course content, for example, the use of games, has also gainedattention. One key question for researchers has been how to facilitate the learning ofprogramming without introducing a gap between the educational and industrial realms[Kelleher and Pausch 2005]. Research focusing on content (e.g., games) has sought toincrease students’ engagement in programming and thereby to improve their learning(see, e.g., Leutenegger and Edgington [2007]).

Holistic pedagogic studies are less frequent, although the need for such studieshas been clearly articulated [Berglund and Lister 2010]. A recent trend of this kindis the attempt to place students in an active instead of the more traditional, pas-sive information-absorbing role (see, e.g., Vihavainen et al. [2011]). One example ofsuch emerging teaching models is “the inverted classroom” or “the flipped classroom,”where the contact teaching traditionally devoted to lecturing is expended on supporting

Authors’ address: V. Isomottonen and V. Tirronen, Department of Mathematical Information Technology,P.O. Box (35), FI-40014 University of Jyvaskyla, Finland.Permission to make digital or hard copies of part or all of this work for personal or classroom use is grantedwithout fee provided that copies are not made or distributed for profit or commercial advantage and thatcopies show this notice on the first page or initial screen of a display along with the full citation. Copyrights forcomponents of this work owned by others than ACM must be honored. Abstracting with credit is permitted.To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of thiswork in other works requires prior specific permission and/or a fee. Permissions may be requested fromPublications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 (212)869-0481, or [email protected]© 2013 ACM 1946-6226/2013/06-ART6 $15.00

DOI: http://dx.doi.org/10.1145/2483710.2483711

ACM Transactions on Computing Education, Vol. 13, No. 2, Article 6, Publication date: June 2013.

6:2 V. Isomottonen and V. Tirronen

students’ in-class activities. The students acquire the necessary information on thecourse topics in the form of self-study outside class hours.

Overall, the present-day movements that emphasize self-direction, such as the Khanacademy1 and its postulate “learn what you want, when you want, and at your ownpace,” challenge formal educational institutions to providing flexible ways of studyingthat match the current social environment. We find that this change in educationalthinking encourages action research of which the present study is an example.

Our approach resembles the inverted classroom, but rather than inverting learningactivities, our thinking has been informed by the notion of self-directed learning. Wewould prefer students to drive their own learning and to prompt learning that is ori-ented toward course topics as opposed to preset course standards [Klug 1976]. Withthis agenda in mind, we designed a course with no lectures, exams, or grades—instead,the course consists of programming and program reviews. We are interested in the stu-dents’ acceptance of these course arrangements and, in particular, what kinds of issuesemerged during a course requiring self-direction. This article presents the results ofour first action research cycle.

2. SELF-DIRECTED LEARNING

The idea of self-directed learning has its roots in many different phenomena, includingreactions to behaviorism, an interest in minority rights, technology development, inter-nationalism, and the increasing size of the school and university population [Gremmoand Riley 1995]. Drawing on Candy [1991], self-direction refers to the learner’s abilityto evaluate and make decisions within a particular domain of knowledge. This implieslearner autonomy, meaning that the control of the learning process is transferred fromthe instructor to the learners. Self-directed learning is often closely associated withinformal learning and life-long learning.

Encouraging self-directed learning is a challenge. Merely taking an active role maymean a great change in the learner’s study habits and cause anxiety [Akerlind andTrevitt 1999]. Successful self-directed learning may require a proper orientation phase[Taylor and Burgess 1995] and still take time to mature [van den Hurk et al. 1999].Furthermore, self-direction has been argued to be a situational matter. A student canbe highly self-directed in one subject of study but much more dependent on expertdirection in another [Grow 1991].

Grow [1991] emphasizes that when a teaching style does not match the learner’sdegree of self-direction, problems are likely to arise. He gives an example of a highly self-directed learner encountering a highly directive teacher, which can cause the learnerto rebel and become bored and the teacher to judge the learner as uncooperative. Onthe other hand, self-direction should not be imposed on those who prefer to depend onthe instructor. As Rogers [1983, p. 154] puts it, there should be provision for those whodo not want freedom and prefer to be instructed. To overcome these kinds of challenges,a responsive teacher role is obviously required.

The ability to be self-directed is affected by many factors. Kim and Park [2011] stud-ied advanced nursing practices and found self-esteem and belongingness to contributeto self-direction. The study by Fry [1972] on first-year psychology students focusedon the effects of different learning styles and found that high-ability students withhigh inquisitiveness perform well in a setting requiring self-direction. Yet anotherchallenging variable is group work. On the one hand, it can constrain individuals’freedom, as mentioned by Faltin et al. [2002], while on the other hand, it can pro-vide both a safe peer learning context [Gibbs 1981] and a source of information forinformal learning [McCartney et al. 2010]. All in all, there is no universal formula

1http://www.khanacademy.org/.


Teaching Programming by Emphasizing Self-Direction 6:3

for supporting self-directed learning, as there are always many variables in action[Gremmo and Riley 1995].

2.1. Teaching Approaches Emphasizing Self-Direction

Within programming education, studies can be found that emphasize active learningwith the characteristics of self-direction. One way to activate students has been throughthe introduction of technology into classrooms. For example, Pears and Rogalli [2011]engage students in collaborative code development workshops and test the students’knowledge throughout the classes. This is done using a smartphone interface, whichallows for individualized feedback. The authors refer to this means of instruction bythe term active pedagogy.

Vihavainen et al. [2011] emphasize a type of active learning in which most of thestudents’ time is expended on exercises. Another constructivist idea they adopt is thecognitive apprenticeship. In practice, this means that worked examples are preferredover showing completed example code and that guidance is always available duringthe exercise sessions. In this way, viable problem-solving strategies are demonstratedto students and student problem solving is directed toward such strategies. In theexercise sessions, students mark completed exercises on checklists; this allows themto monitor their own learning processes. Checklists are available on the Web allowingthe students to compare with each other. Three small bi-weekly exams also enable thestudents to monitor their own learning.

The study by Boyer et al. [2008] focused on investigating self-direction in program-ming education. Teaching is based on students’ questions, which allows the teacher tocover topics that are relevant for the current course population. Peer learning is centralin this Web-based course, which is implemented using a shared learning platform. Astudent who is picked to solve a programming assignment takes a keyboard and pro-grams the assignment in the presence of others, and so demonstrates problem-solvingstrategies at a peer level. Thus, the study provides an example of how peer learningtakes a central role in a context that is less formal than the traditional classroomsetting.

The closest approximations to our course model are probably “the inverted classroom”or “the flipped classroom.” These terms refer to settings where students acquire theinformation they need outside class hours (e.g., from podcast lectures), while the classhours are devoted to activities that have traditionally taken place outside the class[Gannod et al. 2008]. The experiences reported by Gannod et al. are positive, although,as suggested by the authors, managerial issues, such as the time needed for preparingthe learning activities, may arise. Their students responded positively to the severalquestions that validate the course model, while there are indications of challenges thatneed to be addressed. For example, Gannod et al. [2008] write the following.

From the standpoint of student perceptions, the inverted classroom appearsto be well-received, although the suggestions indicate that the acceptancelevel is not unanimous. The suggestions also point to the recognized needthat the viewing of lectures must be incentivized in order to provide motiva-tion for students to prepare for in-class exercises.

The other interesting details in the study are that over a half of the 22 respondentsagreed on the suggestion to use podcasts to supplement class lectures instead of replac-ing them, and that 92% of the 16 respondents agreed that the class should not rely soheavily on podcasts. Such observations motivate the rather critical lens through whichwe review our exercise-driven course with its emphasis on self-study based on a widerange of materials. Our aim is to identify the key research questions that will informour subsequent action research cycles.



2.2. Criticism of and Our Emphasis on Self-Direction

Self-directed learning is occasionally associated with unguided discovery learning,which has consistently produced strong objections. For example, Kirschner, Sweller,and Clark [2006] warn that minimally guided approaches can cause cognitive loadthat hinders learning, and support this claim by referring to an extensive body of em-pirical evidence. Sweller et al. [2007] insist that it is always more efficient to providelearners with information and solutions directly than through any degree of discoverylearning, the latter of which is prone to be associated with the constructivist teach-ing approaches such as problem-based learning (PBL). Furthermore, they state thatthe topics such as group work should be directly taught as opposed to teaching themembedded in real-world problem-solving tasks.

The criticism leveled at minimally guided approaches by Kirshner, Sweller, and Clarkhas prompted several responses from authors advocating PBL. For example, Smithet al. [2007] and Hmelo-Silver et al. [2007] emphasize that constructivist teachingapproaches (e.g., PBL) do not imply unguided instruction or conflict with the humancognitive architecture, as claimed by Kirschner et al. [2006]. Rather, student learningprocesses are monitored and an appropriate degree of instruction (scaffolding) can beprovided. Smith et al. argue that PBL does not only emphasize the acquisition of directknowledge but also the development of the ability to prepare for future learning.

We would stress that our reliance on self-directed learning should not be misinter-preted to mean that our aim is pure discovery learning or minimally guided instruction.We are willing to provide proper support for self-directed learning and to investigatestudent views of our course in the context of the debate on guided versus unguidedlearning.

Our emphasis on self-direction relates to the self-determination theory (SDT) [Ryanand Deci 2000]. This theory considers human motivation and personality by under-lining the human need for competence, relatedness, and autonomy. According to SDT,these three factors enhance constructive social development and personal well-beingand can be emphasized by avoiding such conditions that undermine intrinsic motiva-tion: tangible rewards, deadlines, directives, pressured evaluations, and imposed goals[Deci et al. 1999].

Furthermore, we find the discussion by Klug [1976] relevant to SDT. Klug questionsgrading and the degree system by pondering how learners’ study processes are proneto be directed by the external expectations set by academic standards. In other words,in their studies, learners are easily directed to focus on aspects which will (directly)assist them to fulfill externally given expectations (e.g. pass an exam), a practice whichmay be in conflict with the learner’s personal intellectual development.

SDT and the work of Klug have informed and motivated our course design withrespect to our aim to promote student-drivenness, and emphasize the philosophicalposition on teaching adopted in our study, that is, enabling over assessing. Overall,these references motivate educational research on the social conditions that fosterversus undermine development, performance, and well-being.

3. PROGRAMMING COURSE EMPHASIZING SELF-DIRECTION

3.1. Background and Motivation

At our department, students in all the study lines (educational technology, softwareand telecommunication technology, and computational science) usually take two ba-sic programming courses (CS1 and CS2). These can be complemented with severalbachelor’s- and master’s-level elective programming courses that include Web pro-gramming, programming for graphical user interfaces, programming for mobile ter-minals, an advanced course on object-oriented programming, a theoretical course on



Table I. The Course Learning Topics

TopicLanguage constructsInduction & RecursionLazy evaluationFirst order functionsUse of advanced type systemsBasic persistent data structuresType classesFunctors & Applicative functors MonadsParallel computationProblem solving in FP

programming languages, and a master’s-level course on functional programming (FP),which is the course studied in this article. This course is worth 6 credits and spans 12weeks, during which the learning topics in Table I are studied. The exercises on thesetopics range from simple recursive tasks such as writing the merge sort algorithmto challenging projects like applying monadic structure for writing modular recursivedescent parsers. After the course, we expect students to be able to complete such tasksand to continue to study FP topics independently. Most of the students who took thecourse during our research period had taken both CS1 and CS2, although there werea few (13%) who had taken only CS1. The student course feedback indicates that theytook this course to further broaden their view on programming.

Our motivation for formulating a new teaching model for the FP course was based onobservations from previous lecture-based course instances. First, teaching resourceswere expended on issues that students could have easily studied by themselves (e.g.,syntax and basic structures with the FP language Haskell). Second, it was observedthat students had difficulties in following the more complicated structures during thelectures, as they had not yet realized the need for these structures through program-ming work. We thus observed “waste,” that is, resources were not efficiently utilized tosatisfy students’ needs. Such observations gave rise to the action research reported inthis article.

3.2. The Course Model

The course model that we used to emphasize student self-direction is depicted inFigure 1. The course is divided into weekly cycles of independent study interleaved withtwo contact sessions and is driven by exercises. At the end of each week, the teacherannounces a new set of exercises for the forthcoming week. The first contact session(Practice Session) is intended to help with the difficulties students have encountered,and the second contact session (Review Session) is intended to provide feedback onthe student solutions, after which the cycle begins again with a new set of exercises.

We thus emphasize a challenge-first mindset, where the student is given the exercisesfirst and then directed to work on solving them. This can be compared with the invertedclassroom by Gannod et al. [2008], who found that students should have been incen-tivized to watch podcasts (thus to learn from materials) on their own when preparing forin-class activities. In our exercise-driven course, all of the self-study should be immedi-ately motivated, as the exercises that require learning from materials are given first.

To put the emphasis on student-drivenness, we formalized a “question-makingprotocol,” which the students should use to direct the course by asking questions at acertain time during the week. The protocol begins after the teacher has announced anew set of exercises for the forthcoming week. After the students have independentlystudied the exercises and identified difficult and interesting topics, they can request (by



Fig. 1. The course design.

e-mail) these topics to be elaborated during the first contact session of the forthcomingweek.

Students continue to work on the exercises in the form of independent study betweenthe two contact sessions. The student solutions are delivered to the teacher before thereview session, which enables the teacher to give proper feedback and examine in-teresting student solutions in comparison to example solutions during the reflectivereview session. The two contact sessions are intended to give structure to the coursesuch that both the teacher and the students have the time needed to fulfill their rolesin preparing or answering questions.

With our challenging topic of functional programming, we decided to rely on groupwork (peer learning) as an additional source of learning. In an attempt to create bal-anced and functional groups, we preferred to form groups in which the students bothhad a similar skill level and did not know each other before the class. We devised astrategy where students are singled out randomly to explain the work of their group inthe review session, which we hoped would drive the sharing of solutions (peer learning)within the groups before the session. Additionally, we tried to stimulate self-directionby including reflective questions in the weekly exercises.

With this course model, we decided to focus all our effort on the programming tasksand program review and do away with everything else. We used no exams or grades,and we started the research exploratively with the initial requirement that the studentgroups must complete all the given exercises to pass the course.

The course design decisions were informed by the literature. SDT and Klug encour-age implementing a course without imposed goals (e.g., numeric grades). Likewise,we considered that group work might contribute to relatedness, support, and peerlearning among the students, and that focusing teaching according to the students’questions might be a workable approach (see Section 2). The course design is discussedin Tirronen and Isomottonen [2011].

4. METHOD

The method of our study is action research [Lewin 1946], which is a wide researcharena encompassing a variety of foundations and intentions [Herr and Anderson 2005].Action research focuses on the improvement of social practices and situations, wherethe transformation of social reality is induced by action taking [Carr and Kemmis 1986;Clear 2004]. While action researchers emphasize social change as a study outcome, theyalso accept that transformation of social reality cannot be achieved without focusing



on the understandings of the people involved [Carr and Kemmis 1986, p. 181]. In theeducational context, action researchers are often teacher-as-researchers who aim toimprove and understand their educational practices, and improve the situations wherethese practices take place [Carr and Kemmis 1986, pp. 167, 180].

Action research is often divided into three categories: technical, practical, and eman-cipatory (critical) (see, e.g., Carr and Kemmis [1986], Grundy [1990], McCutcheon andJung [1990]). This categorization is associated with the concept of cognitive interestsin the critical social theory of Habermas, while a similar categorization is present inseveral more general taxonomies on research paradigms [Clear 2004]. Technical per-spective points to the solving of predefined problems with scientific procedures. Prac-tical perspective tackles problems that arise in the study context and aims to developunderstanding of the practices that can solve such problems. Emancipatory perspec-tive refers to the aim of emancipating participants in the action from the dictates ofcompulsions of tradition.

We aim to develop a course model and an understanding of the model in whichthe emphasis is on self-direction on the part of students. At the present stage of ouraction research, we identify with the practical action research perspective where weinvestigate the course by interpreting student responses in relation to our own subjec-tive experiences. Considered from an organizational-historical perspective, we identifyin our aims a transformation in which certain traditional teaching conventions aredropped (lectures, exams), starting from local motivations (see Section 3.1), and wherean understanding of a new setting evolves—this is in line with the emphasis of actionresearch on the historical process of transforming practices and understanding of them[Carr and Kemmis 1986, p. 182].

The emancipatory perspective will receive attention in our future work: At present,we can potentially induce enthusiasm for self-directed (informal) learning in a formalacademic context, which in turn necessitates discussion in our local setting withregard to the implications of our experiences for prevailing organizational-educationalstructures [Robinson 1994]. We would also point out that the results of the presentresearch are able to raise focused questions, which can then be studied in a controlledway (thereby including the technical perspective) during the succeeding actionresearch cycles.

The research goal of the present study is to investigate student engagement in learn-ing programming with reference to our course model. In particular, we are interestedin issues that inhibit students’ learning processes in a setting requiring self-direction.We do not directly measure learning with objective measures [Lister 2001], which wefind to be reasonable only after the key issues have been identified (i.e., during thefuture iterations of this research). Consequently, attributes such as the pass rate andstudent preferences regarding the course arrangements give us information about en-gagement, and thus our references to these attributes should not be taken as implyingan attempt to evaluate learning.

Lewin’s [1946] original paper on action research described the cyclic nature of asocial inquiry that aims to improve practice, with each cycle consisting of a planning,action taking, and reflective phase. In this article, we report the results of our firstaction research cycle, where we adopted a highly exploratory approach to be able tolearn what challenges emerge with the course arrangements we chose to use.

We surveyed the students’ views on the course arrangements three times. Thesesurveys will be referred to as Survey 1, Survey 2, and Survey 3. For the exploratoryresearch approach, and the vagueness of the notion of self-direction (see Section 2), wedid not develop a strict conceptual framework from which to derive the survey questions[Miles and Huberman 1984]. Rather, the selection of our course arrangements wasinfluenced by educational theory and discourse, and, consequently, the survey questions



mostly investigate student opinion about these arrangements. For example, we foundthat group work could be a helpful source of student-driven learning (see Section 2),decided to base the course on group work, and then included survey questions ongroup work. Teacher observations made during the course were allowed to affect thefinal selection and form of the survey questions, as we did not want a predefinedresearch instrumentation to blind us to issues emerging at the research site [Miles andHuberman 1984, p. 42].

With Survey 1, we studied how groups had functioned and how students saw theirrole as a learner. The survey was conducted on the third week and contained thefollowing questions.

—How would you describe your role in the group?—Does this role challenge you as a learner?—Would you change your role?

Survey 2, conducted a little after the first half of the course, was based on ourobservation that students failed to pose focused questions by which they could havedirected the course and meet their specific needs. We studied why this was the caseand what features of the course the students had found instead to be of greatest help.The following questions were included.

—Is there enough learning material/information available to support your learning?—If not, how would you change the course in this respect?

—What has been the biggest help during the course?—Which of the exercises have been most useful . . . least useful?—We have received very few questions. What might be the reason for this (tips: “I

don’t dare,” “questions are difficult to formulate,” “there is no time to,” “everythingis clear”)?

With Survey 3, conducted at the end of the course, we wanted students to summarizetheir experience. We contrasted our course arrangements with the more traditionalones and included general questions which were intended to reveal the uppermostissues concerning the students’ learning processes.

—How did you like FP (as a topic, not as a course)? (The analysis of this question isomitted in this article, as it relates more to our interest in teaching certain aspectsof functional programming.)

—What changes would you suggest for the course to better support your learning?—I would take the course (select boxes with comment fields):

—alone . . . in a group—lectured . . . by programming the exercises—with grades . . . with no grades (pass or fail)

—Describe your motivation during the course.

The analysis of the open-ended answers followed the pattern coding process in thequalitative data analysis (see Miles and Huberman [1984, pp. 67–69]). Pattern coding(thematization) means identification of explanatory reoccurring regularities (themes)that the research site suggests to the analyst. This reduces data into a smaller numberof analytic units. Accordingly, we go through the survey answers by raising severalaspects (lower level themes) that we could identify in the data, and then conclude theanalysis of each survey by discussing what we interpreted to be the most informa-tive theme(s). Further, toward the end of our analysis, we highlight particular (three)themes that we interpreted as reoccurring across the three surveys and consideredbeneficial for our subsequent action taking. While we previously noted that some ofthe survey questions were informed by the literature, the data analysis itself was thus



data-driven. All the data were tabulated and the themes that emerged were extractedon the basis of similarities and differences in the data through multiple iterations: Theanalyst extracted the themes in the data and also compared new data extracts with thethemes extracted so far. The new data segments informed the previously found themesand the analysis process became an iterative one. While the present study is definitelynot a grounded theory study, the analytical process with its focus on emergent issuesresembles grounded theory data analysis, in particular the open coding of the data,where categories are developed by comparison [Glaser 1978].

As well as analyzing these survey data, we summarize the observations and conclu-sions made by the primary teacher of the course (the second author). This will clarifyhow well we were able to adhere to our initial plan, why some adjustments occurred,and what the biggest challenges experienced by the teacher were. We divided the workso that the first author analyzed the student data, the results of which were then dis-cussed in the light of the experiences of the primary teacher. Discussion on the resultsof the analysis of the student data took place after the teacher’s view had been authen-tically documented. Our objective in doing this was to first give genuine attention bothto the teacher’s view and to the views of the students. The action research communityacknowledges the reflection of teachers as an important tool in educational improve-ment [Klafki 1988, pp. 236, 243]. The results section starts with the teacher’s view tofurther set the context in which the students were surveyed.

We should also make it clear that in the current state of our action research, where theresearch approach is exploratory and interpretivist, we are not principally concernedwith quantification and statistics. Frequencies are provided as additional references,while the principal interest is in qualitative aspects that can inform our subsequentaction taking. In our view, we must be self-conscious about when to work with fre-quencies [Miles and Huberman 1984, p. 215]. We can emphasize content analysis withthe help of statistics in future stages of the research, after we have been informed bythe focused research questions raised by the present study and have observed moreiterations of the course. Altogether, relative thinking is present in our analysis in thatcertain higher level aspects emerged repeatedly in the survey data and as such theywere considered to be very “capturing” and explanatory themes.

With regard to the generalizability of the results, we acknowledge the local nature ofaction research, meaning that variation in the social–cultural conditions can give rise toissues other than those reported in this article. Thus, it is not assumed that the researchresult is context-free, that is, generalizable in the classic sense of the word [Lincoln andGuba 1985, pp. 110–128], but can principally benefit those attempting to implementsimilar course models. We would rather employ the naturalistic generalization, whichis intuitive, empirical, and based on personal direct and vicarious experience (see thediscussion in Lincoln and Guba [1985, pp. 110–128]).

5. RESULTS

5.1. The Teacher’s View

This section summarizes the course through the voice of the primary teacher of thecourse.

5.1.1. Completion of the Course. In previous instances of the course, passing the coursewas based on an exam. With our new model, the course began on the assumption thatto pass the course, students should do all the exercises given them. However, because Iwas running the course for the first time, I had to learn what number of assignments itwas reasonable to require of the students during the course. I finally relaxed the initial“do all” requirement and passed all the groups who had completed, on average, at least80% of the weekly exercises.



Although I found no clear way to compare between the two rather different courseinstances, the new teaching model appeared to engage students better. In the previousinstances, the pass rates were 61% (2008) and 43% (2009). For our redesigned course, 48students registered and 41 attended a starting lecture where the course was introducedto students. We lost a few students after the starting lecture but gained some new onesafter the first practice session. Altogether, 35 students passed the course, increasingthe pass rate to 85%. During the first third of the course, the groups completed nearlyall the exercises given, and later, even with the most difficult topics, the completion ratewas well over 50%. During the last weeks, the students performed at a slightly lowerlevel compared with the early stage of the course, probably owing to fatigue. For onegroup with three students, I had to give extra exercises at the end of the academic periodto be able to accept their performance as “pass.” The rest of the student cohort passedthe course, in my subjective view, with skills ranging from acceptable to extraordinary.All of those who failed had dropped out during the course.

5.1.2. Deviations from the Course Plan. Relatively few changes were made to the courseplan, apart from two bigger issues.

We planned to realize student drivenness by responding to the questions receivedthrough the question-making protocol described in Section 3.2. Although the studentshad difficulties with the exercises, I soon noticed that they were unable or unwilling topose questions. In this instance of the course, I received less than 10 questions (in total)in conformity with the protocol. Because there were so few questions, I was unable toprepare a summary of the topics causing difficulties for the first contact session eachweek, as originally planned. I compensated for this by preparing short topic videos onthe basis of what I observed during the contact sessions, which was possible since thestudents did raise informal questions during both weekly contact sessions.

The second major deviation from our plan was the review session, where I felt obligedto adopt a more relaxed atmosphere. I did not assign exercises to students at randomduring the session, which was our initial plan. Similarly, I did not monitor whether thestudents shared their understanding of the exercises within their groups before thesession. This change was made due to my strong feeling that making people explainarbitrary questions at random would not harmonize with the mood of the currentstudent cohort. Instead, it emerged that groups as opposed to individuals presentedsolutions to the exercises during the review session.

5.1.3. Providing Feedback. As we had no lectures and our question-making protocolfailed, I felt there was no opportunity for giving the kind of feedback that wouldproperly support the students’ learning. For example, while the students were ableto complete most of the exercises, there was too little dialogue going on to enablereflection on the quality of the results. Hearing the solutions of other groups duringthe review sessions was not a sufficient remedy, as this kind of information tendedto be inaccurate—often the students’ solution to a given exercise was functional, butneither elegant nor efficient. My hypothesis is that this, in part, explains the students’wishes to receive more example material. These observations led us, as researchers, toconclude that we had introduced some discovery learning, although this was not ourgoal.

Furthermore, I found that the busy weekly cycles (Figure 1) stood in the way ofquality feedback. As the more formal comments on the students’ work were given atthe end of the weekly cycle, during the review session, the students had hardly anyopportunities to apply this new information to the exercises they had already done.

5.1.4. Effect on Workload. This course instance had 10 student groups and some 6 to 15exercises were given per week. This resulted in up to a hundred or so lengthy answers



each week. Going through this pile of material on a weekly basis in order to createfeedback that would be relevant for the entire class was arduous. Even seeminglyminor details such as badly named directories in the returned exercises accumulatedinto large boilerplate tasks, diverting precious hours away from the actual subjectmatter. During the course, I read around 10,000 lines of code. It now appears to usthat giving feedback in the form of summaries for the entire class was a nonscalablesolution.

Rather than making sense of what the whole of the current student cohort needs, Ishould have focused on individualized (and group-specific) feedback. This would mostlikely be easier, since the task of summarizing can be dropped and the exercise reviewcould be, in part, automated by means of technology (see, e.g., Auvinen et al. [2009]).This would also allow dropping the review session in favor of a more efficient trainingsession, since personal feedback can be delivered through other channels. In any event,I need to reconsider the form of feedback in relation to the teacher’s workload.

5.1.5. Course Materials. In this course instance, we had two electronic books, a size-able set of exercises, and a large body of unordered material, such as additional bookchapters and Web-based texts, such as blogs that the students could study of their ownaccord. Based on the student feedback I received, it seems that two elements are morecritical than others: exercises and examples.

In a course model of this kind, which was driven, if not by the students, then bythe exercise sets, it is very important to get the exercises correct. Badly formulatedexercises were observed to cause anxiety, as the students were fooled into thinkingthey are spending time on superfluous details instead of a core course topic. I also feelthat the usual challenges in exercise design were present, for example, how to makethe exercises interesting and suitably challenging (scaffolding).

Although there are enormous amounts of example code easily available on the Inter-net and in the course books, a restricted set of examples that has the teacher’s blessingto help the students not to drown in the material should be available. The tight coursetimetable simply does not allow the students to evaluate what part of the unorderedcollection of available material is currently relevant to them.

Finally, one minor change that ended up having a large beneficial effect on the coursewas the introduction of an IRC channel. The channel provided instant messagingbetween the students and the teaching staff during off-course hours. This channelended up functioning practically every hour of the week, with some students fromprevious course instances participating on a regular basis. This provided studentswith support with the course topics and technical problems at home.

5.2. Survey 1

This section summarizes our analysis of the students’ answers to Survey 1. Of the 25respondents, 21 allowed their answers to be used in the research.

5.2.1. How Would You Describe Your Role as a Learner? We identified the following groupwork patterns from the viewpoint of an individual learner.

(1) A student works independently and the group provides a safety net when difficultiesemerge (14%)

(2) A student takes care of their own learning in a satisfyingly functioning group; astudent both teaches and learns from others (33%)

(3) On top of taking programming tasks, a student is in a team leader role monitoringthe practical aspects of group work (19%)

(4) A student does random things without taking responsibility for group work and, ifneed be, simply copies solutions from others (10%)



(5) A student tries but is challenged all the time, desperately hanging on to a lifebelt(14%)

(6) A student rushes to complete the exercises in order to get a chance to work as heor she feels appropriate (5%)

(7) Previous experience gives a student a dominant role (5%)

We interpret items 1–3 (66%) as indicating healthy group work where learners cantake control of their own learning. Items 4 and 5 are clearly problematic with regardto the individual’s learning, and do not demonstrate or enable self-direction. Item6 indicates that a student takes an active role but is constraining the work of theother group members. Item 7 indicates that variation in initial skill levels dictatesthe group dynamics, inevitably giving experienced students more responsibility. Thiscan overload experienced students and constrain the learning of other group members.Those representing items 4 and 5 are often satisfied enough with their role, as it fitstheir current life situation, giving them a chance to attend to some degree and learnsomething.

Student: This role matches my current life situation well. It is an enormousrelief to me that I do not need to program all the tasks by myself.

5.2.2. Does this Role Challenge You as a Learner? The students’ answers indicate thegroups had already self-organized. Of the 21 students, 16 said they had been challengedas a learner in their group, one could not tell, and the remaining four said they had notbeen challenged. The students in this last category had previous experience of FP, andfor this reason, the first topics of the course, focusing on syntax and basic conventionswith Haskell, were probably easy for them. As indicated by the group work patterns inthe previous section, a few students were already in trouble with the level of challenge.It appears that to better support individual learning processes, we should allow a fasterwalk-through of the topics (weekly cycles) for experienced students and rethink how toallow for more practice time for slower ones.

5.2.3. Would You Change Your Role? Altogether, 18 out of the 21 students did not want tochange the role they currently had in their group. Of the remaining three, one indicateditem 4 and one item 5, as given in Section 5.2.1. The third student simply noted thathe or she would need to practice the version management tool used in the course, to beable to use that skill in doing the group work. None of the three students blamed thecourse or their group members but referred to personal challenges related to time andskill.

5.2.4. Conclusions. It appears that individual learning processes are not that wellsupported in an intensive course run in fixed cycles. First, we found that studentsalready familiar with FP experienced idle time. Second, we identified group workpatterns that were likely to constrain individuals’ learning. With regard to the latter,it is important to note that it is likely that it is not only the group work situationsbut the need to keep up with the pace of the course that constrains learning. That is,mismatch between an individual’s learning process (time and skill) and the pace of thecourse may manifest itself and become emphasized in the group work.

Student: I do programming tasks at my own pace, I’m so slow in doing thetasks that I wouldn’t want to change my role in the group.Student: I do what I can and try to heed the advice given by the more advancedstudents. I try to do my best. I try to keep up with the others.

In Section 5.1, it was noted that teaching, in particular giving sufficient feedback tostudents, was also constrained due to the constant and rapid pace of the course.



We could redesign the course to enable students to choose between group work andindividual work. Furthermore, group work could be used merely to provide support forindividuals, who would all complete the exercises according to their own personal goals.In relation to such student-set individual goals, we should consider how to increaseflexibility so as to allow both repetition of difficult topics and faster progress with easytopics.

5.3. Survey 2

Replies to Survey 2 were received from 22 students, of whom 21 gave permission fortheir use in research.

5.3.1. Is There Enough Learning Material/Information Available to Support Your Learning? Basi-cally, all 21 students reported that there was enough material, but they quite consis-tently mentioned challenges experienced with it. Of the 21 answers, 13 (62%) indicatedissues that could be categorized into the themes below. In five of the remaining eightanswers, the wording of the answer also revealed a slight hesitation. The three clearlyaffirmative answers indicated that a student was self-directed in finding help from thegroup or Internet resources. We extracted the following issues (themes) from the 13answers.

—Students would need clear examples to be able to make sense of the challenginglearning topics (15%).

—Students find it difficult to locate the essential information they would need forunderstanding the current learning topic (38%).

—Students find it difficult to make a proper synthesis of the material (15%).—Students do not have sufficient time to properly make sense of the material; dis-

cerning what information is essential and making a synthesis of it take a lot of time(8%).

—Students find learning from materials to be a burdensome task (8%).—Short topic videos provided by the teacher were reported to be useful and some

students hoped for lectures that would serve to introduce the course topics (15%).

We see all of these items as relating to one major issue (theme): the task of making asynthesis of the learning topics. This issue prompts an important question: Who is re-sponsible for making/providing the synthesis—the teacher or the students? Clearly, theattribute of time in the students’ learning processes is closely related to this question,as active learning based on self-help appears to be burdensome and time-consuming.

5.3.2. . . . If Not, How Would You Change the Course in This Respect? The majority of theresponses indicated that there should be more examples. Students would appreciatethe provision of examples that are as simple and illustrative as possible, in orderto make sense of the challenging topics. We conjecture that this would have mostlikely helped the students in synthesis making. Furthermore, students would like tobe able to mimic the style used in illustrative examples, a request that might relate totheir particular learning styles in the context of learning new and difficult things inprogramming.

An interesting detailed observation is that the reported need for lectures also arisesalong with this question, which again highlights the issue of synthesis making: We ob-serve a student preference for being provided with a ready-made synthesis of the topicsinstead of being required to create it by themselves. We conclude that the students’learning processes (self-direction) are constrained by their previous habits, and hencewe would need to explicitly orient them toward new ways of studying. This interpre-tation is in line with a student comment that directly included a request for educationon the use of materials.



Student: Well, information acquisition with Haskell could be better demon-strated at the beginning . . . or those who appear passive should at least beprompted to identify proper information sources.

5.3.3. What Has Been the Biggest Help during the Course? The students mentioned what-ever materials they can find on the Internet, electronic books, their group, IRC chan-nels, topic videos prepared by the teacher, the weekly practice session and the reviewsession, copying from others, Hoogle (Haskell API search tool) and Google, and the mo-tivating talks given by the teacher. Roughly speaking, some emphasized self-help witha wide range of materials, whereas some placed more stress on support gained fromother people. It is interesting that for some students the biggest help was asking ques-tions during the practice session and being present in the discussional review session.It seems that some of the students got help for synthesis making, in particular, in thediscussional review session and associated this session with a lecture—that, however,comes too late in the weekly cycle.

Student: The demonstration, or the practice session, where you can programand make questions. The lectures, or the sessions, where it is lectured on howthings should be done, albeit in retrospect.

It seems that students would need to have theory first but cannot make a propersynthesis (see the theory) on the basis of self-help and the materials available. However,we also see that students have difficulties in adopting new ways of studying, and theyinsist on seeing things as they used to be.

5.3.4. Which of the Exercises Have Been Most Useful . . . Least Useful? Students liked theexercises that they felt were sufficiently clear and specific as well as the ones wherethey made their own programs. The more interesting the exercises were, the moreuseful they were perceived to be. Further, frustration emerged with overly difficultexercises and with those where an external learning topic, like program testing orgeometry, occupied a more central place than the topics of FP and Haskell. No clearpatterns emerged in the students’ preferences, meaning that one student’s dislikes maybe the likes of another.

An interesting point emerges from the following student quote.

Student: The least useful have been the reflection tasks, as these matters arecovered in the review session.

This illustrates student reluctance to the task of reflection that we would associate withsynthesis making. This again suggests that, for students, synthesis making may appearas a wholly new experience. Another important detail concerns exercise sequenceswhere the task to be done depend on the solutions to the previous ones. These canhinder the division of work within a group and hence needs to be taken into account inthe future.

5.3.5. We Have Received Very Few Questions. What Might be the Reason for This? As statedin Section 5.1, students did not direct the course with questions as we had expected.There are many reasons for this. The students did not dare to ask questions, as theyconsidered it to be their responsibility to resolve problems. Sometimes they knewthey could resolve a problem, given sufficient time, which created a barrier to askingquestions. Some students found the practice session to be an appropriate informalcontext for asking questions. Thus, rather than following a guided question-makingprotocol, the students relied on what they felt to be informal question-making contexts.It appears that they relied on a wide range of information sources in their learning(see Section 5.3.3) but least on the formal question-making protocol suggested by us.



Another challenge has been the difficulty of formulating questions. When studentsdo not yet possess a proper theoretical understanding of the learning topic, they find itdifficult to come up with an appropriate question. This again relates to the issue raisedin this section: synthesis making and the skills it requires.

Student: Coming up with a question requires at least some theoretical under-standing behind it. Thus questions rely on things you know already. Still aweak understanding of the topic does not enliven a poetic vein. Compare thisto asking an octopus to put on tights.

Furthermore, when students come up with questions, this does not match the presetquestion-making protocol in our weekly cycle (see Figure 1). It was probably unrealisticto expect students always to make sufficient progress with the exercises early on andthereby be able to frame useful questions before our first weekly contact session.

5.3.6. Conclusions. Above all, Survey 2 raised the issue of synthesis making in the con-text of active self-directed learning. Due to the failure of our question-making protocol, acomponent that would support students’ conceptual understanding of the topics earlyduring the weekly cycles was missing. However, as our analyses indicate, students’habits were also constrained by the expectations they currently held about studying,which in turn can be assumed to have constrained their self-directed synthesis making.

Students wanted to learn by example. To contribute to students’ synthesis making, wecan clearly benefit from the design of examples and exercises that are both interestingto them and properly scaffold their learning. Concise examples and other materialscould compensate for the fact that self-directed active learning takes time, which is agreat challenge when a course like this is run according to the usual academic timeunit (here, 12 weeks).

5.4. Survey 3

Survey 3 received replies from 19 students, 18 of whom gave permission for their usein research.

5.4.1. What Changes Would You Suggest for the Course to Better Support Your Learning? Thestudents would have preferred more examples, more simple examples, better instruc-tions for exercises, and more concise materials. Some called for an introduction to thetopic (FP) at the beginning of the course, and some would prefer one lecture each weekbefore doing the exercises. These confirm the challenges we identified in Survey 2 (thequestion of synthesis making).

In addition, the students requested more supervision time along with structures thatwould force shared schedules in group work. In Section 5.1, we notice that the teacherexperiences indicated an already high teaching workload, while yet more supervisionwould have been welcomed, and conclude that workload has also presented a challengefor the students. One student would have liked to know the minimum amount of workneeded to pass the course, which is likely to indicate frustration with a rather informalstudy context.

5.4.2. In Group . . . Alone? A clear majority of the respondents preferred group workover individual work (67%) (see Table II). The students contrasted their group workexperience with their previous group work experiences and noted that group work waslikely to be a successful arrangement in this course where all of the participants hadat least some motivation toward the topic.

Compared with Survey 1, devised earlier in the course, we found stronger commentson the group work in both a positive and negative sense, as the students had nowencountered the most difficult topics on the course. On the one hand, group work



Table II. The Students’ Preferences of the Course Arrangements at the End of the Course When Contrastedwith Traditional Lectured Courses

N = 18In Groups Alone Both With exercises With lectures Both No grades Grades All the same

12 3 3 12 1 5 9 1 8

See the survey questions in Section 4. Students could select more than one option.

served as a safety net from which the students got necessary help and as an incentivenot to drop out from the course. In particular, the former was our conscious aim, givensuch a challenging topic as functional programming.

Student: Impossible without the support of the group

On the other hand, those who preferred individual work had experienced an unequalskill level or differences in the commitment such as to cause problems. As might havebeen expected, our strategy of placing students with the same level of prior experiencein the same group was not successful in all cases.

Student: Although experience of group work is valuable, the workload is heretoo arbitrarily divided.

According to some students, the first part of the course could have been completedindividually, while the remainder of it benefited more from group work. Obviously, thisfollows from the increasing difficulty in the exercises.

Our conclusion drawn on the basis of Survey 1 was confirmed. That is, we couldprofitably allow both individual and group work and find a way to use group workprimarily as a support tool so that each student completes the exercises individually.

5.4.3. With Exercises . . . with Lectures? Learning by programming was preferred over lec-turing (67%) (see Table II). This was experienced as educative and motivating comparedwith a lecture-based option; the students considered that learning programming re-quires a hands-on approach. We find that the one student who would have preferredlecturing also reported a negative group work experience. Those who suggested thatboth are needed hoped for a few support lectures during the course. Two of those whopreferred exercises also commented that both are needed. The need for support lectureswas indicated by our analyses of Survey 2, in particular regarding the question of whois responsible for making a synthesis of the learning topics. We return to this questionin Section 6.

5.4.4. Grades . . . No Grades? Half of the students preferred no grades, whereas one stu-dent specifically hoped for grades on account of their motivating effect. The remainingeight answered in the middle and said they did not really mind one way or the other. Thesum of those who preferred no grades and those who had no strong opinion amounted to94% of responses (see Table II). Those who preferred no grades said it motivated themto work more than they otherwise expected to, and avoided unnecessary cramming.One student reproduced exactly our motivation for not grading, that is, that the ideaof the course was not set the standards to be met but to provide a context for learning.

Student: The course did not emphasize particular aspects of Haskell → it isnicer to decide on your own learning.

At the end of the course, the students were asked whether they would prefer gradesor pass-or-fail also in a face-to-face contact session. None of those present opted forgrades. Additionally, they were asked to correspond by e-mail if they wanted to vote onthis matter privately. No e-mails were received.



5.4.5. Describe Your Motivation during the Course. The students enjoyed the practicalityof the course and made favorable comparisons with other courses. They valued thechance for hands-on work, which was experienced as educative. Some were inspiredby the Haskell language, but some said their motivation was reduced because they didnot know how useful learning Haskell would eventually be.

The answers principally raise one matter, which is the same that we already putforward in Section 5.2: how to keep up with the pace of the course. When studentsrun into difficulties, the rest of the course tends to be about surviving it. Problemsaccumulate and students start to lose their motivation.

Student: The problem was the sequence of tasks, which started from the“rectangles” [refers to a particular programming task] . . . If you start to haveproblems they accumulate later

It is not always the difficulty of the programming tasks but the students’ current lifesituation that would necessitate a lower pace during the course. As we have emphasizedearlier, the time factor occupies a central role in the students’ learning processes.The students say this time/learning pace-related challenge was compensated for bythe support gained from group work, by the attraction of the Haskell language, and bythe enthusiasm and the supportive attitude of the teacher and teaching assistants.

5.4.6. Conclusions. With Survey 3, we basically confirmed the conclusions drawn fromthe first two surveys. These were group work as both a constraining and supportingfactor in a setting requiring self-direction, conflict between the pace of the course andthe individuals’ learning processes, and the challenge of synthesis making. A newquestion was grading, a topic which had not really occupied the students during thecourse. All in all, we find that when our course arrangements were contrasted withmore traditional ones, most of the students preferred the present options.

We find that the issues emerging from the student data conform closely to the teacherexperiences described in Section 5.1, which might follow from the close contact betweenthe teacher and students in a course of this kind [Gannod et al. 2008].

6. DISCUSSION AND SUGGESTIONS FOR FURTHER ACTIONS

Taking an action research approach, we have critically reviewed a programming coursethat emphasizes self-direction on the part of students. Despite the difficulties reported,we are encouraged to continue with the research. We saw a considerable increasein the pass rate, and the students preferred the present course arrangements to moretraditional ones. The goal of our practical action research was to develop understandingof our course model, in particular to find out what issues arise in a learning settingrequiring self-direction. The main issues that we identified are:

(1) students’ opportunities for self-direction in a group work setting;(2) mismatch between individual learning processes and the hurried pace of the course,

the latter of which was implied by academic course scheduling; and(3) the challenge of supporting students’ synthesis making.

To avoid the group work obstacles reported in this article, we will, in our next imple-mentation of the course, show students the group work patterns discovered here. This,we hope, will enable the students to self-regulate their role in the group. Furthermore,we will allow the students to choose between individual and group work. We will guidethose who select group work to find group mates who not only have similar previousexperience but also similar resources and schedule. Above all, we aim to design groupwork so that help is available at a peer level but each individual completes the ex-ercises. This conforms to Thelen’s [1949] view that, following from the postulate of



experiential learning, an individual’s first-hand learning experience may be preferredover an individual’s “being in the audience,” while social interactions are known tovaluably expose the individual’s thought processes to criticism and consequences. Ifwe take programming as the fundamental skill in computing, then the emphasis onindividual work over being in the audience should be well reasoned in our course.

We found that running the course in fixed time cycles necessitated a constant workpace from the students. Thus, while we heavily emphasized active participation (pro-gramming) with no lectures, we did not really consider how to support individuallearning processes. In this sense, our teaching model still resembles a lectured course;it is the attribute of time that we need to focus on. In the future, we will continueto provide contact sessions during one academic period but increase the overall timespan of the course to cover a full semester. In this connection, we will formulate theweekly exercises as compact modules to enable course work that is flexible and easyto grasp. All the modules will be available to be worked on at the beginning of thesemester. With these changes we hope to allow for rapid progress on easy topics andincreased practice time for difficult ones on an individual basis. The attribute of time ispresent in the recent sociology literature, where the speeding up of life and the relatedscarcity of time are under debate [Wajcman 2008]. By making the course more flexible,we aim to adjust our teaching to today’s social environment. Here, we set the researchquestion of whether increased flexibility decreases the problems related to time andskill or whether we begin to see study motivational issues.

Perhaps the most interesting issue we located concerns students’ difficulties withmaking a synthesis of the learning topics. Our observations on students asking forsupport lectures resemble those by Boustedt et al. [2011], who found that some studentsvalue formal learning (when contrasted with informal learning) for the experience,deeper knowledge, and structure provided by an instructor. We need to ask if we triedto force informal learning into an academic time unit or forced discovery learning withtoo little time available for it. We found two aspects that relate to these questions. First,we would have needed to better orient the students to the study habits required byour course model to properly set their expectations. Encouraged by the study by Taylorand Burgess [1995], we should demonstrate the study skills needed and leave room forsharing and discussing precourse experiences. We assume the latter could contributeto the emergence of self-directed study groups. Second, our question-making protocolwas not successfully realized, and hence we will need to rethink how the students’theoretical understanding (synthesis making) of the learning topics can be supported.Students appeared to prefer informal question-making contexts, which we need toemphasize in our subsequent research.

We will begin to address the question of synthesis making by redesigning the exam-ples and exercises with the cognitive load theory [Sweller et al. 1998] as the guidingtheoretical framework. This is encouraged by Miller and Settle [2011] who also referto this theory. They studied how different ways of studying affect learning and foundconceptual questions about examples and self-study based on examples to producegood learning. In contrast, as found by Miller and Settle, the situations where stu-dents could mimic the answers from examples were not that successful. The authorsconcluded the latter did not challenge students’ cognition toward the construction ofuseful transferable knowledge.

The cognitive load theory proposes that tasks introducing unwanted cognitive loadshould be replaced by ones that induce construction of useful schemas, by which alearner is able to apply a newly acquired understanding in new situations. It is alsoworth noting that prior to being able to deal with challenging meanings in the learningmaterial, some automation of knowledge structures may be required (compare this



to learning letters versus being able to understand meanings in a text). From thesestandpoints, and based on the findings by Miller and Settle, during the first weeks ofthe course, we will increase the number of exercises in which students answer con-ceptual questions about the given examples. This could show the students a sufficientnumber of examples of “what constitutes a Haskell program” and thereby contributeto the automation of knowledge structures concerning the basics of Haskell. In sum,we will try to contribute to the students’ synthesis making by relying on self-studywith examples, a portion of which could consist of short topic videos where the teacherprograms the examples. A set of examples would then serve as the primary learningmaterial, enabling a good connection between the material and the design of the exer-cises. We will investigate whether these improvements in materials allow us to retaina very active role on the part of the students in synthesis making and reduce the timeneeded for it.

We feel that our exploratory start with action research has been successful. Thisarticle highlights three issues that can be taken into account when implementing astudent-driven course. With the design ideas and research questions raised here, weare in a more informed position to continue with the research. The design of the nextaction research cycle will merit a separate study.

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Received April 2012; revised January 2013; accepted February 2013


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Teaching Programming by Emphasizing Self-direction-ACM-ToCE