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Effectiveness of an Interactive Learning EnvironmentUtilizing a Physical Model
Shane Brown, M.ASCE1; Andrew Easley2; Devlin Montfort3; Jennifer Adam4; Bernard Van Wie5;Adesope Olusola6; Cara Poor, M.ASCE7; Cory Tobin8; and Alicia Flatt9
Abstract: The goal of this study is to evaluate the effectiveness of a physical desktop learning module and associated activities and assess-ments (DLM&A) implemented in an undergraduate engineering class. Preassessments and postassessments designed as part of this studywere implemented within a control group that participated in 11 interactive lecture sessions covering open channel flow, and an experimentalgroup that participated in nine lectures and two 50-minute sessions with the DLM&A. Student responses on assessments provide strongevidence to suggest students’ conceptual understanding increased significantly when the DLM&A is implemented. The experimental groupregistered a gain of 0.57 out of 1.0 possible, with 70% of the students achieving minimum competency, compared to a respective 0.26 gainand 39% competency for the control group. The average effect size for the experimental group was d ¼ 0.98. Qualitative assessments showexperimental group students were much more likely to correct their conceptual justifications on written responses than control group students.DOI: 10.1061/(ASCE)EI.1943-5541.0000197. © 2014 American Society of Civil Engineers.
Author keywords: Innovative pedagogy; Educational assessment; Active learning; Hands-on learning.
Introduction
Many studies in engineering education have shown increased learn-ing benefits from implementing an active learning classroom envi-ronment compared to traditional lecture (Connor and Goff 2001;Prince 2004; Chi 2009). An active learning environment is gener-ally where students are doing something other than listening toa lecture, but the level and types of activity in active learning
environments vary greatly from occasional implementation ofa think-pair-share exercise to a studio-based learning environmentwhere there is little or no lecture. We have developed a hands-onlearning apparatus, termed a desktop learning module (DLM), as-sociated activity worksheets, and preasessments and postassess-ments for open channel flow that is based upon best practices inactive learning (henceforth the DLM and associated activitiesand assessments are referred to as DLM&A). The approach incor-porates hands-on learning, an interactive learning environment, andformative assessment, and collectively represents a highly activelearning environment at the little or no lecture end of the spectrummentioned above. Hands-on learning promotes the direct manipu-lation of a system (Abdul et al. 2011; Connor and Goff 2001). TheDLM&A guide the student to manipulate open channel parameterssuch as channel slope, flow rate, and channel obstructions and ob-serve resulting changes in the flow profile. Interactive learningallows groups of students to work together on a task that cannotbe accomplished effectively by any one individual (Chi 2009).Formative assessment allows for immediate feedback from fellowstudents, teaching assistants (TAs), and the instructor without pen-alty (Nicol and Macfarlane-Dick, 2006), providing a safe and re-source-rich environment for asking questions and constructingknowledge. It is proposed that a learning environment with thesethree characteristics combined and applied to concepts of openchannel flow will result in improving students’ conceptual under-standing of fundamental concepts. The DLM&A learning envi-ronment is a unique blend of hands-on learning with activitiesdesigned to promote interactive discussions between students.
By conceptual understanding the authors refer to the kind ofknowledge that students use when explaining or predicting phe-nomena (Vosniadou 1994). The need for conceptual understandingresearch is largely based on the finding that students often developthe ability to use equations and perform calculations without under-standing what they mean or being able to apply them to newcontexts (Vosniadou, 1994; Carey 2000; Duit and Treagust 2003).The ability to deal with new problems during professional prac-tice using a fundamental understanding of phenomena and theiranalyses is vital to the practice of engineering, which makes the
1Associate Professor, School of Civil and Construction Engineering,Oregon State Univ., Corvallis, OR 97331 (corresponding author). E-mail:[email protected]
2Research Assistant, School of Civil and Environmental Engineering,Washington State Univ., Pullman, WA 99164-2910. E-mail: [email protected]
3Assistant Professor, School of Chemical, Biological, and Environmen-tal Engineering, Oregon State Univ., Corvallis, OR 97331. E-mail: [email protected]
4Assistant Professor, School of Civil and Environmental Engineering,Washington State Univ., Pullman, WA 99164-2910. E-mail: [email protected]
5Professor, Voiland School of Chemical Engineering and Bioengineer-ing, Washington State Univ., Pullman, WA 99164-2710. E-mail:[email protected]
6Assistant Professor, Dept. of Educational Leadership, Sports Studies,and Educational/Counseling Psychology, Washington State Univ.,Pullman, WA 99164-2136. E-mail: [email protected]
7Clinical Associate Professor, School of Civil and EnvironmentalEngineering, Washington State Univ., Pullman, WA 99164-2910. E-mail:[email protected]
8Student, School of Civil and Environmental Engineering, WashingtonState Univ., Pullman, WA 99164-2910. E-mail: [email protected]
9Teaching Assistant, School of Civil and Environmental Engineering,Washington State Univ., Pullman, WA 99164-2910. E-mail: [email protected]
Note. This manuscript was submitted on January 16, 2013; approved onNovember 5, 2013; published online on January 7, 2014. Discussion periodopen until June 7, 2014; separate discussions must be submitted for indi-vidual papers. This paper is part of the Journal of Professional Issues inEngineering Education & Practice, © ASCE, ISSN 1052-3928/04014001(10)/$25.00.
© ASCE 04014001-1 J. Prof. Issues Eng. Educ. Pract.
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development and identification of conceptual understanding imper-ative to engineering education (NRC 2005).
The purpose of this study is to evaluate the effectiveness of theDLM&A on improving students’ conceptual understanding using amixed methods comparative case study design (Yin 2003). A mixedmethods research design provides a rigorous and valid approachto measuring DLM&A effectiveness by triangulating numericaland verbal data to build a credible case (Teddlie and Tashakkori2009). The research design features the following aspects: (1) acontrol and experimental group that are very similar with the ex-ception of the DLM&A implementation, (2) development and im-plementation of preassessements and postassessments to measureconceptual understanding, and (3) a combination of quantitative,comparative improvement including t-test and effect size calcula-tions, and qualitative analysis of student written explanations.
Methodology
Overview
In this study the effectiveness of the DLM&A in terms of fosteringstudents’ understanding of fundamental open channel flow con-cepts was investigated using a preassessment and postassessmentcomparative case study design. Participants in the comparativecase study were chosen from offerings of Water Resources Engi-neering, a required junior-level undergraduate engineering courseat Washington State University. A description of the participantgroups and the timing of their participation are shown in Table 1.Improvement was evaluated through assigning numerical scores tothe preassessments and postassessments as well as qualitativeanalysis of students’ written justifications of their answers.
Equipment and Curriculum Development
Interviews with Students to Identify Conceptual DifficultiesThe DLM&Awere developed based on results from clinical inter-views with 50 students on open channel flow concepts includingflow profiles, hydraulic jumps, flow transitions, and the hydraulicand energy grade lines during the spring term prior to the experi-ment described in this paper, and from feedback from four engi-neering faculty members.
The interview protocol (summarized in Table 2) was constructedto investigate students’ in-depth understandings of open channelflow concepts using a semistructured clinical interview approach(Greenspan 2003; Sommers-Flanagan 1999). This approach con-sists of a core set of questions with individualized probing ques-tions to investigate students’ deeper understandings. An initiallist of difficult concepts was developed and refined through meet-ings with two civil engineering faculty members who had taughtwater resources engineering and fluid mechanics. The list of con-cepts was used to develop core and probing interview questions.
Each interview was audio recorded and professionally tran-scribed. The transcriptions were imported into the qualitative datasoftware NVivo, and each student interview packet, which included
a figure and a written response, was scanned and linked to theirrespective transcription. Student explanations and written re-sponses were coded for each question to identify areas of concep-tual difficulty. A list of difficult concepts was developed bysummarizing student answers and rationale for their answers.For example, when participants were asked to explain how depthwould change for an abrupt supercritical drop transition, over 60%of the interviewed participants answered incorrectly and could notprovide detailed explanations. The list of concepts was used fordevelopment of the DLM&A.
Development of the Desktop Learning ModulesThe DLM&A’s intended use involves small groups of students inthe classroom, rather than in the laboratory. At its most basic level,the DLM conveys fluid, includes a reservoir, pump, and flow meter,and can be used with open channels or closed conduits. In the flume(i.e., open-channel) configuration in Fig. 1, piping goes from theexit of the pump to the entrance of the flume. Water exits the flumedirectly into the reservoir. Dimensions of the DLM base unit areapproximately 41 cm left to right, 23 cm from top to bottom,and 28 cm front to back. The flume attachment is approximately76 cm left to right, 23 cm top to bottom, and 2.5 cm in width.Graduation marks etched into the flume are used to measure flowdepth registered in English and SI units and are labeled at one-inchintervals with 0.1 inch tick marks, and 1 cm intervals with 1 mmtick marks, respectively. A sluice gate can be inserted just after theentrant feed after the tall portion of the flume, to the right in Fig. 1,to build up static head when needed. As part of the DLM, a digitallevel and flow meter allow students to report the slope of the flumeand flow rate, respectively. The base unit includes a storage area infront of the reservoir. There is also a battery housing unit that ismounted above ground level to prevent short circuiting in caseof a spill.
The design of the DLM was guided by interview findings asdiscussed above specifically to be able to demonstrate physicalphenomena related to areas of conceptual difficulty. For example,because students had difficulties with subcritical drop transitions,the DLM was designed to demonstrate this phenomenon.
Development and Implementation of the AccompanyingWorksheetsUtilizing best educational practices and results from the interviewsrelated to flow profiles, hydraulic jumps, flow transitions, and hy-draulic and energy grade lines (HGL/EGL), the authors developedactivities to include in two worksheets to be used over two classperiods. The DLM&A sessions include hands-on learning, com-monly considered to be physical manipulation of a system or ex-periment (Abdul et al. 2011; Connor and Goff 2001), by examiningthe combined effects of varying flow rate and slope, and creating upto eight different profile configurations. This can be considered aninteractive learning environment, which is characterized by work-ing in a group, either physically or verbally, to achieve one commontask, and has been shown to be effective on student learning(Chi 2009; Salomon and Perkins 1998). The worksheets weredeveloped such that all students were required to be engaged,
Table 1. Summary of Overall Schedule and Participant and Professor Information
Term Participant group/purpose ProfessorNumber ofparticipants
Spring 2011 Student interviews after course: identify misconceptions and develop concept assessment 1 50 (94%)a
Fall 2011 Control course: implementation of common teaching practices 2 41 (87%)Spring 2012 Experimental case: implement DLM in addition to common teaching practices 1 58 (86%)aNumber and percentage of total class population that participated in the study. Some students from each group opted to not have their data utilized in the study.
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e.g., in setting up a hydraulic jump. Formative assessment involvesusing feedback from students and teachers followed by additionalinstruction to improve student learning and to guide the learners’thinking to a clearer understanding of fundamental underlying con-cepts that govern phenomena (Nicol and Macfarlane-Dick 2006).The DLM&A was used to introduce formative assessment by firstasking the students questions about a concept or a process, in whichthe students may be incorrect in answering, and second to allow
them to visualize the process, the results of which may be incon-sistent with what the students thought they would observe. Thisprovides immediate visual and sensory feedback, which causesthem to reconsider their original premises and rethink their under-standing of the underlying concept or process. The worksheetswere not graded, but given a score for participation; i.e., the par-ticipants were assigned points based on their level of effort. Forexample, when participants were asked to draw the HGL andEGL directly on the flume, they were required to try it themselvesfirst and then receive feedback, if incorrect, from an instructor orteaching assistant.
One worksheet details transitions and HGL/EGL while the otherfeatures hydraulic jumps and flow profiles. Each worksheet hasfour sections, as detailed in Table 3: (1) Learning Objectives;(2) Conceptual Pre-Activity; (3) DLM Activity; and (4) Reflection.Sections (1) and (2) were to be completed before the DLM inter-action session; sections (3) and (4) were to be completed during thesessions.
The worksheets were tested and improved for clarity and com-pleteness with three separate focus groups consisting of engineer-ing students two months prior to the DLM&A implementation.Three student volunteers that had taken water resources previously,worked through the worksheets and made detailed notes as to prob-lem areas in each of the worksheets. An example of a change madeas a result of a focus group is providing more explicit directions onhow to simulate a particular physical phenomenon using the DLM.
Development of the Preassessment and PostassessmentsThe final preassessemnt and postassessments consist of sevenqualitative questions, with figures, covering the following con-cepts: flow transitions, flow profiles, EGL/HGL, hydraulic jumps,and channel roughness. The first six questions related to conceptsaddressed in the DLM&A implementation while Question 7 wasunrelated and served as a control question for comparison purposes.Questions were open-ended and required that students predict orexplain fundamental phenomena. Students were given a total of15 minutes to complete the seven-question assessment. Each groupwas given the preassessment one lecture period before the openchannel unit and the postassessment one lecture period after theopen channel unit.
Development of the Assessment RubricDevelopment of the rubric to assign scores to each preassessmentand postassessment was based on established practices (Arter andMcTighe 2001). The rubric is shown in Table 4 and was used toassign a value of 0 to 10 for each question on the preassessment andpostassessments. Participants could be assigned a score of 10 iftheir justification and fundamentals were correct.
Table 2. Summary of Concepts Covered During the Interviews
Concept Questions asked
Open channelflow HGL/EGL
• Draw the HGL and EGL from points A to Ba
• How would you determine how much waterflows from A to B?
• Write the Energy Equation between A and BSpecific energy • How does water transition between A and B?
• How does the specific energy change betweenpoints A and B?
Flow profiles • Draw the flow profiles for A—Db
• Label locations of super/sub/critical flowHydraulic jumps • Draw the flow profiles for A—D
• Label locations where a hydraulic jump occurs• What do you think a hydraulic jump is?
aPoint A was upstream on the diagram; point B was downstream.bA–D represents four flow profiles with different channel configurations.
Fig. 1. A picture of the desktop learning module (image by AndrewEasley)
Table 3. Worksheet Summary
Concept Learning objectives Conceptual pre-activity DLM activity Reflection
Flowtransitionsa
Identify energy and depth changethrough different flow regimes
Draw four different profiles andrelate changes in depth to specificenergy
Model a supercritical drop anddetermine flow regimes
Explain why an understandingof flow transitions is important
HGL/EGLa Understand placement ofHGL/EGL
— Calculate and draw both gradelines
—
Flowprofilesb
Draw flow profiles for multiplechannel configurations
Draw four different hypotheticalflow profiles and explain if ahydraulic jump can occur
Label different flow regimes forthree different modeled profiles
Label different flow regimesfor real-world situations
Hydraulicjumpsb
Explain why hydraulic jumpsoccur and relate to specificenergy curve
Describe and explain hydraulicjumps in own words
Create three hydraulic jumpprofiles and calculate relatedspecific energy
Identify hydraulic jumps inreal-world situations
aDenotes concepts addressed by the first worksheet.bDenotes concepts addressed by the second worksheet.
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Inter-rater reliability was established with three researchersindependently utilizing the rubric to assign scores, followed by ameeting to examine the reliability of the scores. In almost all cases,reliability of the rubric and consistency of score assignment washigh. In a few instances where the reliability was low, discrepancieswere discussed until grading consistency was within 10% amongthe researchers.
A standard gains (G) formula was used, Eq. (1), to normalize theincrease or decrease between each participant’s preassessement andpostassessment score, with 10 being the possible points for eachquestion. A standard paired t-test was performed, as well as a testfor significance to determine if the quantitative gains were statisti-cally significant. The percentages of participants that answeredabove a minimum competency score of 7 out of 10 for each ques-tion’s post-test score was also determined.
G ¼ ðPost − Pr eÞ=ð10 − Pr eÞ ð1Þ
Development of the Qualitative Assessment MethodologyStudents’ written justifications of their answers on the preassess-ment and postassessments were analyzed utilizing the qualitativedata analysis tool, NVivo, and separating the data into codesand nodes. A code is an interpretation of a unit of text that holdsinformation of interest; a node is a group of similar codes. In thisprocess student responses were labeled as correct or incorrect re-sponses. Similar correct or incorrect responses were then groupedand coded for specific words of interest. Finally, a node was createdbased on common words of interest. The following is one exampleof what similar responses entail: Participant 1’s response, “Depthincreases because the change in channel elevation relates to a pos-itive elevation change, therefore y increases”; and participant 2’sresponse, “depth increases between 1 and 2 because the changein elevation gives head to specific energy.” Both participant quotesjustified an increase in depth with reference to a change in elevationand were therefore grouped together to form a node.
DLM&A Implementation
Participant SelectionThree groups of students from three different course offerings par-ticipated in this study, as shown in Table 1. The first group wasinterviewed to develop the DLM&A. The other two groups werethe control and experimental groups. All students were enrolled inWater Resources Engineering, a course emphasizing open channeland closed conduit water flow, pumps and pump systems, and
estimation of components of the hydrologic cycle. Effort was madeto keep the control and experimental course offerings as similar aspossible. Details of the similarities are provided in subsequentsections.
There was a total of 24 groups of three students each participat-ing in the experimental group during the DLM&A interactive ses-sions. While 12 groups were completing 2 DLM&A interactivesessions, the other 12 groups participated in a lecture by a differentinstructor on an introduction to hydrology, after which the 2 groupsswitched. During the DLM&A sessions, three teaching assistantsassisted the professor in answering questions and providing feed-back to the students.
Internal ValidityInternal validity in educational evaluation would be achieved in thiscase when a causal relation between the implementation of theDLM&A and the gains between the preassessments and postassess-ments was established (Gliner et al. 2009). To isolate the effects ofthe DLM&A on student learning, the implementations of the con-trol and experimental courses were made as similar as possible;i.e., although two different instructors taught the control and exper-imental courses, the base coverage of all open channel material wassimilar. This coverage includes teaching style, lecture notes, exam-ples, in-class activities, homework assignments, and examinations.Both groups participated in eleven 50-minute periods coveringopen channel flow. The control group had 11 lecture periods, whilethe experimental group had 9 plus two 50-minute DLM&A ses-sions. Activities conducted in the DLM&A sessions are summa-rized in Table 5. Material about the effect of channel roughnesson open channel flow was used for a control for conceptual learn-ing. Both groups received one lecture and one homework assign-ment on the topic, and participants in the experimental group werenot asked any questions about roughness during the DLM&A ses-sions, nor were they asked to observe or manipulate the channelroughness. Each group received a preassessment and postassess-ment on the topic. Most lecture sessions for both the control andexperimental groups also included some form of active learning, inthat students received in-class activities where participants workedwith peers to complete an example problem, thus promoting smallgroup discussion and instantaneous feedback.
All participants had completed the prerequisite fluid mechanicscourse before enrolling in Water Resources Engineering, and there-fore had similar educational background knowledge in open chan-nel flow concepts. Additionally, the preassessment scores werecompared and no statistically significant differences were foundbetween the two groups.
Table 4. Generalized Rubric for Assigned Scoring
0 points 1 point (low) 3 5 points (medium) 7 9 points (high)
No answer Correct with noexplanation
Explanation isstrongly flawed
Explanation is relatedto fundamentals
Explanation relates tofundamentals strongly
Provides clearexplanation
Or Or Or Or Or OrNo reasoning Correct/incorrect
w/incorrect logic50–75% criticalmistakes/incorrect
25–50% criticalmistakes/incorrect
25% criticalmistake/incorrect
1 simple mistake
Table 5. A Summary of the DLM Activities for Each Open Channel Flow Concept
Key concept DLM session coverage
Flow profiles Placed a sluice gate and broad crested weir into the flume while observing the effects on the water level profileFlow transitions Placed a supercritical drop transition and observed the effectsHydraulic and energy grade lines Drew the HGL and EGL on the flume using transparenciesHydraulic jumps Placed various weirs in the flume while manipulating the channel slope and/or flow rate to produce hydraulic jumps
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Results
Quantitative Results
As summarized in Fig. 2, and Table 6, the experimental group out-performed the control group on all six DLM&A related questions.For these questions the experimental group registered statisticallysignificant increases in gains and mean postscores adjusted forsmall differences in prescores, with p-values less than 0.001 inevery case. The average gain and adjusted mean postscores forall questions except the control were 57% and 66%, respectively,for the experimental group. Corresponding averages for the controlgroup were 26% and 40%, respectively. For the control question,there were no significant differences between the experimental andcontrol groups in the gain or adjusted mean post scores with a cor-responding p-value of 0.114.
Table 6 also provides details on the t-test values, effect sizes,(which measure the practical relevance of the differences betweenthe experimental and control groups), average scores, and the num-bers and percentages of students scoring above a minimum com-petency of 7 out of 10 for each question. T-tests show statisticalgains for the experimental group on all DLM&A related questionsas indicated above with all p-values less than 0.001. There is a large
average effect size, d ¼ 0.98, with a range of 0.77 to 1.38 betweenthe six experimental questions for the differences between exper-imental and control group adjusted mean post-scores. This meansthat the average participant in the experimental group registeredlarger adjusted mean scores than 84% of the participants in the con-trol group (Coe 2002). On the other hand the small effect size of0.12 for control Question No. 7 indicates that only 54% of the par-ticipants in the experimental group registered adjusted mean post-scores that were higher than the participants in the control group,i.e., adjusted means were nearly equally distributed. On the preas-sessment, nearly all students in both the experimental and controlgroups were below minimum competency with only five control(1.8%) and two experimental (0.5%) participants scoring abovea seven for any of the responses on all six questions, not includingthe control question. After instruction 70% of the DLM&A partic-ipants were deemed to be above minimum competency for the setof six questions, while only 39% of the control group was aboveminimum competency. By contrast, for the control question, 56%and 51% students began above minimum competency for the con-trol and the experimental groups, respectively. On the postassess-ment there was a much smaller difference between the two groupswith 68% and 79% deemed competent for the control and exper-imental groups, respectively, which will be discussed later. Whentaking this information collectively there is strong evidence to sug-gest the statistically significant increases in gain and adjusted meanpost tests, the higher percentage of students above minimumcompetency, and large effect sizes registered for the experimentalover the control group can be attributed to implementation ofthe DLM&A.
Qualitative Results
In the following subsections the authors discuss more detail onstudent reasoning for three of the six questions, one from eachof the three main concepts, and a brief description of the correctanswer. These questions were chosen as representative examplesfrom each of the three main concepts covered in the preassessmentsand postassessments (specific energy, HGL/EGL, and flow pro-files). A summary table provides the details of conceptual under-standing pertaining to each question. Finally, representative studentwritten explanations are included in each section to demonstrate thedifference in justification of answers between the control and ex-perimental groups and to provide evidence of students’ conceptualchange.
Fig. 2. Differences between the control group (dark gray bars) andexperimental group (light gray bars) gains [see Eq. (1)] for eachquestion. Question 7 is a control question (Note: * denotes significantdifferences between groups; p-value <0.05)
Table 6. Summary of Statistical Data Representing Improvements in the Experimental Group Compared to the Control Group
Question GroupAdjusted meanpost-scores
Standarddeviation T-value P-value
Effectsize
Preassessment competencyabove 7 (%)
Postassessment competencyabove 7 (%)
1 Transitions Control 1.8 2.23 5.6 <0.001 1.38 1 (2%) 5 (12%)Experimental 5.9 3.49 0 40 (69%)
2 Transitions Control 3.6 2.68 3.8 <0.001 0.77 0 9 (22%)Experimental 6.1 3.56 0 29 (50%)
3 EGL/HGL Control 2.9 2.66 4.1 <0.001 1.06 3 (7%) 10 (24%)Experimental 5.5 2.20 1 (2%) 44 (76%)
4 Sluice gate Control 5.0 1.87 5.4 <0.001 1.04 1 (2%) 24 (59%)Experimental 6.9 1.79 1 (2%) 48 (83%)
5 Broad weir Control 5.4 2.14 3.9 <0.001 0.81 0 15 (37%)Experimental 7.2 2.13 0 38 (66%)
6 Hyd. jump Control 5.5 2.91 3.0 <0.001 0.85 0 21 (51%)Experimental 7.7 2.19 0 46 (79%)
7 (Control)roughness
Control 3.7 2.63 1.6 0.114 0.12 23 (56%) 28 (68%)Experimental 4.1 2.53 29 (50%) 46 (79%)
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Flow Transitions: A Subcritical Drop
Question prompt: “How does depth change between points one andtwo in Fig. 3?” The written prompt described the flow regime assubcritical, and noted that the triangle marked the water surfacewhile the hatched line indicated the channel bottom.
The specific energy curve in Fig. 4 and the specific energy equa-tion, [Eq. (2) shown below] are needed to answer this question.
E2 ¼ E1 þΔZ ð2Þ
E is defined as the total energy in the system above the channelbottom and ΔZ refers to an abrupt drop in the channel bottom.Because Fig. 3 shows an abrupt drop under subcritical flow, thedecrease in channel bottom elevation corresponds to an increasein specific energy at point (2) using Eq. (2). Participants thenhad to use the specific energy curve to see that an increase in spe-cific energy on the subcritical branch of the curve results in an in-crease in depth.
Participants spent most of one DLM&A session, about35 minutes, placing a supercritical drop transition in the flumeand working through the associated worksheet. They were askedto perform calculations to identify the flow regime as supercriticalor subcritical, and to describe the change in depth observed dueto the drop transition. Students in the control group received
one lecture period, one example problem during lecture, and onehomework problem related to the transitions concept.
The majority of participants who scored below minimum com-petency did so because they attempted to answer using the conceptof velocity. They argued that velocity increases as the slope in-creases, which led them to assume that the depth decreases as re-quired by continuity. Forty students from the experimental groupscored above minimum competency with no preassessments aboveminimum competency. A total of 18 students referenced velocity inthe preassessment, while only five referenced it in the postassess-ment. The control group did not show a similar change in reason-ing, with approximately half of the students referencing velocity inthe preassessment and postassessment. A brief summary of Ques-tion 1 answers and student quotes is displayed in Table 7.
The Hydraulic and Energy Grade Lines
Question prompt: “Draw the hydraulic grade line (HGL) and en-ergy grade line (EGL) for the channel profile shown in Fig. 5.” Thewritten prompt described the channel geometry and slope as con-stant, and noted that the triangle marked the water surface while thehatched line indicated the channel bottom.
For participants to answer this question correctly they needed toknow the difference between the HGL and EGL and what specificterms and types of energy were associated with each grade line. TheHGL includes the elevation head and depth; the EGL includes theelevation head, depth, and velocity head. A correct answer wouldshow the HGL along the water’s surface, because the elevation plusthe depth is exactly equal to the water’s surface elevation, while theEGL is parallel to the HGL and a distance of V2=2 g, the energydue to velocity expressed in head, above the HGL in a uniformchannel.
Participants interacted with the DLM&A and displayed their rel-ative understanding of HGL/EGL concepts by drawing the gradelines on the flume using transparencies. Once each group had col-lectively finished this step, an assistant checked their work and in-structed them in this informal setting if the students had mademistakes or had questions. The control group received about 10 mi-nutes of lecture covering the HGL and EGL, approximately thesame time allocation allowed the experimental group. They hadno homework on the concept, and only saw a diagram during lec-ture. It is worth noting that despite the differences in how HGL/EGLs and flow transitions were covered in the control group, stu-dent gains in both concepts were very similar.
The majority of participants who answered this incorrectly didso because they mixed the terms related to the HGL and EGL.Some indicated that the EGL was above the HGL and both wereabove the water surface. Fundamentally, this means that the partic-ipants who answered with this reasoning did not understand that thepressure for an open channel flow system is water depth (Y) whenthe reference point is the channel bottom. After approximately20 minutes of one DLM&A session, the experimental groupwas better able to correctly answer this question, increasing from
Fig. 4. The specific energy curve, a relationship between flow regimes,flow depth, and specific energy, is required to analyze this problem
Table 7. Summary of Question 1 on the Transition Elevation Change Presenting Control and Experimental Common Answers and Quotes
Question 1 summary Control postassessment Experimental postassessment
Proportion of correct answers 5=41 (12%) 40=60 (69%)Most common answer 21 participants emphasized changes in velocity, and incorrectly
assumed that increased velocity causes decreased depth25 participants referred to changes in specificenergy and the flow regime (subcritical flow)
Representative participantwritten explanation
“Depth decreases since velocity increases because goingdownhill, it speeds up”
“Depth increases due to ΔZ increasing and ifstarting in subcritical flow, this causes an increasein depth. E2 ¼ E1 þΔZ”
DATUM
1 2
Fig. 3. Open channel with changing bottom depth
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1 to 44 of 58 students meeting minimum competency between thepreassessment and postassessment. Also, they were less likely toconfuse the critical concepts. Specifically, 23 experimental groupparticipants confused the HGL and EGL in the preassessment,while only one did so in the postassessment. The control groupdid not show a similar change in reasoning and actually showedan increase, from one to seven, in the number of participantsindicating the incorrect profile on the postassessment. A briefsummary of Question 3 answers and representative participantwritten quotes are displayed in Table 8 below.
Flow Profiles: Supercritical, Subcritical, and CriticalFlow
Question prompt: “Draw the most accurate representation of theflow profile in Fig 6. Label locations of subcritical, supercritical,and critical flow, and explain your reasoning.” The written promptdescribed the flow regime as subcritical and noted that the trianglemarked the water surface while the hatched line indicated the chan-nel bottom.
The gap between the channel bottom and bottom of the gate issmall enough for the students to assume that the flow depth is lessthan Yc, or the critical depth. Therefore, they would also have toindicate that flow begins at subcritical (deep and slow) and transi-tions rapidly to supercritical flow (shallow and fast) after flowingunderneath the sluice gate. Shortly downstream of this transition,the flow will transition back to subcritical from supercritical via ahydraulic jump, although the students were not required to drawthis downstream transition. As is clearly indicated in the figure(Fig. 6), the flow regime is transitioning based on the specificenergy curve in Fig. 4 starting on the upper part of the graph insubcritical flow and ending on the lower part of the graph in super-critical flow. Avisual representation of the correct answer, immedi-ately after the sluice gate but before the hydraulic jump, can be seenin Fig. 7.
Participants produced this flow profile in the DLM using varioussizes of gates; they also varied the flow rate and slope of the flumeto observe the resulting effects. In addition, there was not onecase where the water surface spilled over the top of the weir; allvariations resulted in all flow traveling underneath the sluice gate.Participants in the experimental group were prompted to draw theprofile they observed in the flume, label the different flow regimes,
label the depth before each flow regime, i.e., y1, yc, and y2, andreport their values of flow rate and slope. Participants in the controlgroup saw a drawing of a sluice gate, similar to Fig. 7, watchedvideos of various flow profiles, and were asked conceptual ques-tions such as ‘where are the places of supercritical, subcritical, andcritical flow for this profile during lecture.
The majority of participants in the control group indicated thecorrect flow profile for this question but used incorrect fundamen-tals. Rather than relating in their answer that “the depth under thegate is less than Yc” or “the fluid is being forced under”, they usedthe relationshipQ ¼ VA, whereQ is flow rate, V is velocity, and Ais the cross-sectional area of the flow. Although Q ¼ VA is tech-nically correct, it cannot be used to answer all questions about flowdepth because it does not provide enough information; further in-formation using specific energy concepts is required. The writtenprompt indicated that the fluid begins in subcritical flow and isunder steady, uniform conditions. Therefore the fluid is forcedunder the gate passing through critical flow into a supercritical flowregime. After one DLM&A session, the experimental group wasbetter able to correctly answer this question, improving from 0to 48 of 58 students with minimal competency between the preas-sessment and postassessment, and they were less likely to use therelationship Q ¼ VA for their justification. Specifically, 20 exper-imental participants justified their response with Q ¼ VA on thepreassessment, while not one of them used this justification inthe postassessment. By contrast more than half, 24 of 41, of thecontrol group participants were still using the Q ¼ VA argumentduring the postassessment. A brief summary of answers andrepresentative participant written quotes can be viewed in Table 9below.
Other Questions
As stated earlier, the above three questions (numbers 1, 3, and 4)are only a representative sample of the six experimental questions.Question numbers 2, 5, and 6 yielded similar results that can beviewed in Table 6 at the beginning of the section. Question 2 askedhow the specific energy, rather than depth, changed between twopoints. The results from Question 2 paralleled the results fromQuestion 1 by indicating a similar improvement between thetwo groups, the control group going from 0% with minimum com-petency on the preassessment to 22% on the postassessment and theexperimental group going from 0% to 50%, with comparable in-creases in the accuracy of their written justifications. Results fromQuestions 5 and 6, on the broad crested weir and hydraulic jump,respectively, paralleled the results from the sluice gate Question 4.After a brief interaction period with the DLM&A, the experimentalgroup increased from 0% to 66% and 79% with competency onQuestions 5 and 6, respectively; whereas the control group in-creased from 0% to 37% and 51% with competency for Questions5 and 6, respectively.
Fig. 5. Open channel profile and datum
Table 8. Summary of Question 3 on HGL/EGL Presenting Control and Experimental Common Answers and Quotes
Question 3 summary Control postassessment Experimental postassessment
Proportion of correct answers 10=41 (24%) 44=58 (76%)Most common answer 7 participants indicated the EGL is above the HGL and both
are above the water surface. There were a total of 9 differentincorrect answers
32 participants had reasoning that correctly placed the HGLand EGL. They also provided the correct terms (Z, Y,V2=2 g) for each grade line. Five participants mentioneddepth results in pressure for an open channel
Representative participantwritten explanation
‘The EGL includes pressure, velocity and elevation.The HGL includes just the elevation and velocity.’Note: Answers were variable in justification
‘Neglecting head loss, the EGL is above the HGL byV2=2 g and has the same slope as the bed. In open channelflow, the HGL corresponds to the water surface becausethere is no pressure.’ Note: students referenced watersurface as datum
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Control Question
Question 7 involved the effects of channel roughness on openchannel flow, and was included in the preassessment and postas-sessment as a control because this concept was addressed onlyin lecture for both the control and experimental groups. The ques-tion described the flow regime as supercritical and at steady state,and stated that all other geometric variables remained constant, butnoted that the rough portion is twice as rough as the smooth por-tion. Participants were subtly prompted to use Manning’s Equation,(which relates velocity to the roughness coefficient) through the useof the variable “n” [see Eq. (3)] to describe channel roughness. Par-ticipants were asked to explain how the roughness of the channelwould affect water depth.
For participants to answer this question correctly, they wouldneed to utilize either the relationship Q ¼ VA or Manning’s Equa-tion as follows:
V ¼ ðKm=nÞR2=3S01=2 ð3Þ
where V = velocity; Km = metric/English unit conversion factor;n = Manning’s coefficient; R = hydraulic radius; and So = channelslope.
Ideally, through noticing that Manning’s Number n doubledfrom the upstream to the downstream end of the channel, V woulddecrease as n is in the denominator in Eq. (3). Because the systemis at steady state, the cross-sectional area of flow in the roughersection would increase according to the relationship A ¼ Q=V.Therefore, depth increases over the rough section.
Table 10 summarizes the data for the control question. Note thatthe most common answer is the same for both groups unlike theother summary tables where the most common answers were in-correct for the control group and correct for the experimental group.The number of participants that answered this question using ap-propriate justification on the postassessment is nearly the same be-tween the control and experimental groups. The control groupshows an increase in numbers of students at or above minimumcompetency from 56% on the preassessment to 68% on the post-assessment, an increase of 12%. The experimental group showedan increase from 50% to 79%, an increase of 29%. Because thepercentages for the control question are quite similar and statisticsin Table 6 show descriptive statistics that lend support to the argu-ment that it is the DLM&A implementation that makes the differ-ence in students producing a correct analysis of scenarios posed inexperimental questions.
Discussions and Conclusions
Quantitative and qualitative data provide strong evidence that theDLM&A is effective as an aid for learning the selected open chan-nel concepts. This is supported by the statistically-significant gains,a difference of 0.26 out of 1.0 possible on average, and a large aver-age effect size d ¼ 0.98 between the experimental and controlgroup responses on experimental questions. In addition, studentsparticipating in the DLM&A session demonstrated a differentand improved understanding of concepts as they changed their rea-soning more often, improving from an average 0.5% above mini-mum competency for the collective set of preassessment questionsto 70% correct for postassessment questions, while participants inthe control group went from 1.8% to only 35% above minimum
Fig. 6. Bottom opening sluice gate
Fig. 7. Correct flow profile and placement of the subcritical and super-critical flow regions; the triangle indicates the water surface. Note that ahydraulic jump will occur just downstream of this profile
Table 9. Summary of Question 4 on the Sluice Gate Presenting Control and Experimental Common Answers and Quotes
Question 4 summary Control postassessment Experimental postassessment
Proportion of correct answers 24=41 (59%) 48=58 (83%)Most common answer The majority of participants indicated the correct flow
profile but justified their answer with Q ¼ VA. Only 9mentioned any reference to flow regime
24 provided a description stating the sluice gate ‘forced’ thewater supercritical or the water height was less than Yc afterthe gate
Representative participantwritten explanation
‘Y [depth] must change, and will flow at the same Q [flowrate] which means V [velocity] increases [so depthdecreases]’
‘When fluid goes under the weir, it is forced to supercriticalflow for some amount of time’
Table 10. Summary of Question 7 on Roughness Presenting Control and Experimental Common Answers and Quotes
Question 7 summary Control postassessment Experimental postassessment
Proportion of correct answers 28=41 (68%) 46=58 (79%)Most common answer The majority of correct responses (19) indicated that the
roughness slowed down the velocity and, using continuityand the relationship Q ¼ VA, concluded that the waterdepth increased
33 participants who answered correctly mentioned theconcepts of roughness and velocity to rationalize theiranswer
Representative participantwritten explanation
‘Roughness will cause more friction, which leads to aslower velocity. Thus increasing the depth of the water’
‘The roughness will decrease velocity and therefore create adeeper depth’
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competency on average. The control question concepts related tochannel roughness were not addressed in the DLM&A sessions, butthere was a lecture covering the concept in both the control andexperimental groups. Correspondingly, differences between the ex-perimental and control group gains were not statistically significantand there was less of a difference between the percent correct on thepreassessment and postassessment for either group with the exper-imental group going from 50% to 79% correct and the controlgroup from 56% to 68% correct.
Although this study presents a body of evidence that theDLM&A was effective in improving students’ conceptual under-standing, it is difficult to know what about the two 50-minutesessions was particularly effective in improving student learning.Particularly problematic is understanding whether hands-on learn-ing, formative assessment, or interactive learning were relativelymore or less influential to the students. Although the control sessionsincluded some aspects other than lecture, including watching videosof open channels and working on problems during the lecture peri-ods, they were still far less active than the DLM&A session.
Chi’s (2009) detailed characterization of effective classroomlearning environments provides some insight into why the DLM&Aclassroom environment was so effective. Chi defines three learningenvironments: active, constructive, and interactive; and presents alarge body of data that indicate that interactive environments aremore effective on student learning than constructive, and construc-tive more effective than active. Active is considered to be doingsomething while learning, such as manipulating an interactive learn-ing environment. Constructive is when students produce additionaloutputs that go beyond the information given, such as asking ques-tions or comparing or contrasting ideas. Interactive is characterizedby benefits derived from interactions with a person or a systemwhile engaged in an activity.
This framework provided insight into the effectiveness of theDLM&A sessions. The control group sessions consisted of passiveactivities such as taking notes, and active activities such as workingon practice problems. In contrast, the DLM sessions were interac-tive. For example, the worksheets prompted students to performcertain experiments with the DLM&A and record observations.Discussions between individuals within the group promoted collec-tive seeking of a better understanding of the concepts governingthe phenomena just observed; such discussions make studentschallenge their own preconceived ideas and offer explanations.Students were also asked to explain certain concepts and receivefeedback from an instructor or teaching assistant and then refinetheir explanations of phenomena observed.
The DLM&A learning environment is unique from those studiesby Chi because of the presence of a small-scale model of a real-world fluid flow phenomenon. Using the DLM&A allow studentsto have direct interaction with a system to display, on a small scale,realistic events that occur in natural and engineered settings.
The fact that two different professors taught the control andexperimental groups is one limitation of this study. Although aseries of meetings were held before implementation of the researchplan to maximize the similarity of the teaching style, lectures,examples, homework, and exams, some differences nonetheless re-mained, e.g., due to the personality of the professors, interpersonalrapport, etc. Also, not all background data, e.g., demographicaldata, grade point average, major, could be collected for eachindividual participant. This information would provide a bettercomparison of the students involved in the control versus experi-mental course offerings. Long-term implementation of the preas-sessment and postassessments in this course, and in similarcourses at other universities, can address these weaknesses. Despitethese issues the authors note that both professors typically receive
above-average student ratings. Also, the professor for the experi-mental group taught the course from which initial interviews wereconducted to determine student misconceptions.
At first the DLM&A may seem difficult to implement, espe-cially for large class sizes. However, the authors’ test case had70þ students and only an 18% shift in course time allocation wasnecessary to yield a significant increase in student’s conceptualunderstanding. The instructor and three students set up and tookdown the DLMs, resulting in approximately 10 minutes total forsetup and take down time. Therefore, the benefits gained by imple-menting the open channel DLM&A, and potentially other DLM&Alike it, in place of a few traditional lectures is at the cost of very littleinstructor time in and out of the classroom. To expand the use ofDLM&A, the authors plan to reconfigure them to improve concep-tual learning for other water resources topics, such as pressurizedpipe flow and hydrologic principles.
A confounding and very important factor in the decision to im-plement the DLM&A or comparable hands-on learning apparatus isthe relative costs of different instructional approaches. Lecturealone is clearly the cheapest approach and correspondingly, at leastif this is the singular approach to teaching and learning, least ef-fective method. Some universities may also currently use or haveaccess to large flumes that can be used for student laboratory ex-ercises. However, these singular pieces of equipment do not allowfor individual interactions with the equipment and interactive learn-ing during this interaction. The equipment cost for the DLMs isabout $500 per unit, and undergraduate teaching assistants wereused at approximately a 20∶1 student:TA ratio and engaged in abouttwo hours of training for the DLM&A. Although the cost is greaterthan lecture and likely than for use of a large flume the educationalbenefits are substantial.
This research argues for the effectiveness of DLM&A in devel-oping students’ conceptual understanding of fluids mechanics con-cepts with a comparison of a lecture section with an interactiveDLM&A session. The intention was not to divisively suggest thatlectures be completely replaced with the DLM&A. Broadly speak-ing the intention was to assess the effectiveness of an innovativeapproach to helping students learn about a phenomenon that is vis-ibly observable. Results presented herein provide further evidenceof the power of an interactive learning environment incorporatinghands on learning. However, results do not suggest that all lecturesshould be replaced with the learning environment described herein.Understanding the optimal balance of lecture and interactive learn-ing environments, particularly in consideration of financial obliga-tions is an area for future research that more holistically considersthe student experience.
Acknowledgments
The financial support of the National Science Foundation undergrant NSF DUE-1023121 is gratefully acknowledged. The authorsare also grateful to Schyler Hect and Lisa Chen who helped with theinitial development of the DLM and associated worksheets. Theauthors give credit to machinist Gary Held of the WSU Collegeof Engineering and Architecture for innovations he provided duringthe construction phase for the DLMs.
References
Abdul, B., et al. (2011). “Addressing student learning barriers in developingnations with a novel hands-on active pedagogy and miniaturized indus-trial process equipment: The case for Nigeria.” Int. J. Eng. Educ., 27(2)468–476.
© ASCE 04014001-9 J. Prof. Issues Eng. Educ. Pract.
J. Prof. Issues Eng. Educ. Pract. 2014.140.
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rary
.org
by
Uni
vers
ity o
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alif
orni
a, S
an D
iego
on
09/1
5/14
. Cop
yrig
ht A
SCE
. For
per
sona
l use
onl
y; a
ll ri
ghts
res
erve
d.
Arter, J., and McTighe, J. (2001). Scoring rubrics in the classroom: Usingperformance criteria for assessing and improving student performance,Sage Publications, Thousands Oaks, CA, 37–44.
Carey, S. (2000). “Science education as conceptual change.” J. Appl. Dev.Psychol., 21(1), 13–19.
Chi, M. T. H. (2009). “Active-constructive-interactive: A conceptual frame-work for differentiating learning activities.” Topics Cognit. Sci., 1(1),73–105.
Coe, R. (2002). “It's the effect size, stupid: What effect size is and why it isimportant.” British Educational Research Association Annual Conf,University of Exeter, England, 12–14.
Connor, J. B., and Goff, R. M. (2001). “Assessment of providing in-class,hands-on, activities to Virginia Tech’s first year engineering students.”2001 ASEE Annual Conf. and Exposition, American Society for Engi-neering Education, Washington, DC.
Duit, R., and Treagust, D. (2003). “Conceptual change: A powerful frame-work for improving science teaching and learning.” Int. J. Sci. Educ.,25(6), 671–688.
Gliner, J. A., Morgan, G. A., and Leec, N. L. (2009). Research methodsin applied settings: An integrated approach to design and analysis,2nd Ed., Taylor and Francis Group LLC, New York, NY.
Greenspan, S. I. (2003). The clinical interview of the child, 3rd Ed.,American Psychiatric Publishing, Washington, DC.
National Research Council. (2005). “How students learn: Science in theclassroom. Committee on how people learn.” Division of behavioraland social sciences and education, M. S. Donovan and J. D. Bransford,eds., The National Academies Press, Washington, DC.
Nicol, D. J., and Macfarlane-Dick, D. (2006). “Formative assessment andself-regulated learning: A model and seven principles of good feedbackpractice.” Stud. High. Educ., 31(2), 199–218.
NVivo Version 9.1.106.0 [Computer software]. Cambridge, MA, QSR.Prince, M. (2004). “Does active learning work? A review of the research.”
J. Eng. Educ., 93(3), 223–231.Salomon, G., and Perkins, D. N. (1998). “Individual and social aspects of
learning.” Rev. Res. Educ., 23, 1–24.Sommers-Flanagan, R. (1999). Clinical interviewing/Rita Sommers-
Flanagan and John Somers-Flanagan, 2nd Ed., Wiley, New York.Teddlie, C., and Tashakkori, A. (2009). Foundations of mixed methods
research, Sage Publications, Thousand Oaks, CA.Vosniadou, S. (1994). “Capturing and modeling the process of conceptual
change.” Learn. Instruct., 4(1), 45–69.Yin, R. K. (2003). Case study research: design and methods, 3rd Ed., Sage
Publications, Thousand Oaks, CA.
© ASCE 04014001-10 J. Prof. Issues Eng. Educ. Pract.
J. Prof. Issues Eng. Educ. Pract. 2014.140.
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y; a
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