Conference Session

ERM Poster Session

Collection

2009 Annual Conference & Exposition

Authors

Dazhi Yang, Purdue University; Ruth Streveler, Purdue University; Ronald Miller, Colorado School of Mines; Aidsa Santiago Roman

Tagged Divisions

Educational Research and Methods

. For example, Part I had8341 words and 11 figures while The Nature of Science had 7342 words and 17 figures. For allthree different modules, there were open-ended reflection questions inserted after each mainsection of instruction in order to facilitate students’ deep understanding of the trainingmaterials.20ResultsAdaption of the schema training modulesResults of the case study indicated that the materials, which were originally used to train middleschool students and undergraduate psychology students in learning science concepts, were welladapted for undergraduate engineering students. Specifically, all four participants (n=4)considered the reading level of the modules is appropriate for undergraduate engineeringstudents, the content is

Conference Session

Student Attitudes and Perceptions

Collection

2009 Annual Conference & Exposition

Authors

Johannes Strobel, Purdue University; Inez Hua, Purdue University; Jun Fang, Purdue University; Constance Harris, Purdue University; Lindsey Tracy, Purdue University

Tagged Divisions

Educational Research and Methods

Page 14.1088.4literature and a general lack of more detailed research into the conceptions and attitudes ofstudents towards environmental and ecological issues, especially how both relate to engineeringcareers.Threshold Concepts and attitudesConceptual change is among the conceptions oflearning that have recently been most closelyembraced by the educational psychology andlearning sciences communities6. Humansnaturally build simplified and intuitive theories toexplain their surroundings. The cognitive processof adapting and restructuring these theories basedon experience and reflection is referred to asconceptual change. Most research indicates thatconceptual change arises from interactionbetween experience and current conceptionsduring higher

Conference Session

Student Learning

Collection

2009 Annual Conference & Exposition

Authors

Thomas Litzinger, Pennsylvania State University; Peggy Van Meter, Pennsylvania State University; Carla Firetto, Pennsylvania State University; Lucas Passmore, Pennsylvania State University; Christine B. Masters, Pennsylvania State University; Stephen Turns, Pennsylvania State University; Sarah Zappe, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

and another part during the second phase. The intention here was that students wouldhave time in between the phases to reflect upon information presented. The Motivated Strategiesfor Learning Questionnaire 25served as the filler activity.Participants in this study were students enrolled in Statics and the intervention was administeredjust prior to the midterm exam. Participation in the study was one of several activities for whichthe students could receive extra credit in the statics class. The intervention and all instrumentswere delivered through the course web site and students could complete the activities at any timeduring each phase. The web-based system randomly assigned students to one of the fourexperimental groups.Table 1. Summary

Conference Session

Student Learning

Collection

2009 Annual Conference & Exposition

Authors

Kathryn Jablokow, Pennsylvania State University-Great Valley; Pamela Vercellone-Smith, Penn State Great Valley; Sally Sue Richmond, Penn State Great Valley

Tagged Divisions

Educational Research and Methods

14.613.9Figure 4: KAI score distribution for male students only Page 14.613.10Figure 5: KAI score distribution for female students onlyIn considering the sub-groups sorted by gender, the male students contained both the mostAdaptive and the most Innovative students in the total sample (as expected from generalpopulation studies19), but the female student group also contained individuals with highlyAdaptive and highly Innovative cognitive styles (within a total range of 79 points). While themale students reflected a distribution similar to that of the general male population (mean of 98),the female students (on average) showed a slight skew towards Innovation when compared to thegeneral female

Conference Session

Educational Research

Collection

2009 Annual Conference & Exposition

Authors

Milo Koretsky, Oregon State University; Christine Kelly, Oregon State University; Philip Harding, Oregon State University; Edith Gummer, Northwest Regional Educational Laboratory

Tagged Divisions

Educational Research and Methods

= 6.94, df = 2)The Critical Thinking category is ranked higher in the virtual laboratories than in the physicallaboratories (64% vs. 42 and 51%). Again, this increase is consistent with the premise that thevirtual laboratories promote high level cognition. Similarly, the statements that were coded asExperimental Design averages 62% for the virtual laboratory. This value is significantly higherthan the first physical laboratory which averages 7%. This result is consistent with theinstructional design of the virtual laboratories, which, in part, is to engage students in an iterativeexperimental design approach that is reflective of the approach used by practicing engineers.2Indeed, a significant portion of instruction was devoted to explaining

Conference Session

Modeling Student Data

Collection

2009 Annual Conference & Exposition

Authors

Gillian Nicholls, University of Pittsburgh; Harvey Wolfe, University of Pittsburgh; Mary Besterfield-Sacre, University of Pittsburgh; Larry Shuman, University of Pittsburgh

Tagged Divisions

Educational Research and Methods

college degree without completing it by the study’send. Other theoretical departures included dying or declining to participate further in the study,but these departure types were eliminated by the design of the data collection. Students werepurged from the study if they died, were not selected for further sample inclusion, could not belocated for the fourth and final follow up (F4), or declined to participate in the fourth follow up.The 12,144 records in the NELS:88/2000 dataset reflected all students that were chosen forinclusion in F4 and responded to the survey. Students who actually achieved a STEM degreenever experienced the event of interest because they did not depart the STEM track. The 12,144records were sorted to remove from analysis

Conference Session

Engineering Design: Implementation and Evaluation

Collection

2009 Annual Conference & Exposition

Authors

Ken Yasuhara, University of Washington; Andrew Morozov, University of Washington; Deborah Kilgore, University of Washington; Cynthia Atman, University of Washington; Christine Loucks-Jaret, University of Washington

Tagged Divisions

Educational Research and Methods

responses toQuestion 3, which asked participants to choose the solution they deemed best from among thealternatives they listed in response to Question 2. Question 3 also asked for solution evaluation,so we expected that it would be more likely than the other questions to make design rationalemore visible. This was the main reason we focused this initial examination for evidence of lifecycle consideration on Question 3 responses.The Question 3 responses were coded using a scheme that reflects a simplified version of lifecycle. Our life cycle model parallels established models (e.g., the Environmental ProtectionAgency’s1) and recognizes the following stages or processes: design, construction, normaloperation, maintenance/modification, and disposal

Conference Session

ERM Potpourri

Collection

2009 Annual Conference & Exposition

Authors

Alexandre Probst, Colorado School of Mines; Aarthi Krishnaswamy, Colorado School of Mines; Vinita Singh, Colorado School of Mines; Barbara Moskal, Colorado School of Mines; Cyndi Rader, Colorado School of Mines

Tagged Divisions

Educational Research and Methods

insulatingmaterials and the impact on heat loss. The insulation materials include straw, felt,and sawdust, all which are readily available in the students‟ environment. Tofacilitate student comprehension, modifications to the parameters result inchanges in the corresponding graphics that reflect the impact in real applications.For example, if students input changes in the thickness of a material, that materialincreases in thickness on the screen.Figure 2: A screenshot of the control panel and animated demonstration ofparameters controlling heat loss rate.A final goal for the software is to encourage students to derive solutions tonumerical problems. Figure 3 displays a screen shot which requires users tomanually input the result of a calculation in a textbox

Conference Session

Using Technology to Enhance Education

Collection

2009 Annual Conference & Exposition

Authors

J. Shelley, United States Air Force

Tagged Divisions

Educational Research and Methods

Website: http://www.esm.psu.edu/dci/ (GrayEt al. 2003). The DCI was administered pre and post course as a timed assessment onlinethrough the Dynamics class Blackboard website. Each semester, the instructor also administered a self-developed exploratorysurvey of 15 questions to assess that semester’s broadcast environment and pedagogy viathe class Blackboard website. While the survey was reviewed by a learning expert andanother faculty at a different university to remove bias and determine appropriateness ofthe questions, a focus group of students was not employed to validate the survey.Approximately 10% of the questions on the survey changed each semester to reflect theexact circumstances of that semester’s class. Questions on the survey

Conference Session

Student Attitudes and Perceptions

Collection

2009 Annual Conference & Exposition

Authors

Sarah Parikh, Stanford University; Helen Chen, Stanford University; Krista Donaldson, Stanford University; Sheri Sheppard, Stanford University

Tagged Divisions

Educational Research and Methods

limited our scope to the current or first choiceof major so as to allow for each student to be counted only once in the cross-major comparisons.Our analysis included only juniors and seniors. We believe these students were more likely thanunderclassmen to graduate in the major they selected (thereby minimizing responses fromstudents who may later decide to transfer out of the major). Furthermore, we expect that juniorsand seniors have completed more major-specific coursework resulting in responses that reflect amore complete picture of the specific major’s engineering curriculum. We did not include 5thyear (or more) seniors in our analysis.In order to determine the effects of collapsing men and women students of both junior and seniorlevel

Conference Session

Modeling Student Data

Collection

2009 Annual Conference & Exposition

Authors

Junqiu Wang, Purdue University; P.K. Imbrie, Purdue University

Tagged Divisions

Educational Research and Methods

was so I knew what to expect from them.PT01 My team was confident in its ability to overcome adversity (e.g., interpersonal conflict, assignments).PT02 I feel a sense of accomplishment in my team's ability to work together.PT03 This team gave me confidence in the ability of teamwork to solve problems.PT04 My team had the collective abilities (e.g., communication, interpersonal, technical) to accomplish course assignments.PT05 I was confident that our team produced acceptable solutions to course assignments.GS02 My team used clear, long term goals to complete tasks. Page 14.249.3GS03 My team reflected upon its goals in

Conference Session

Student Attitudes and Perceptions

Collection

2009 Annual Conference & Exposition

Authors

Holly Matusovich, Virginia Tech; Ruth Streveler, Purdue University; Ronald Miller, Colorado School of Mines; Barbara Olds, Colorado School of Mines

Tagged Divisions

Educational Research and Methods

reflections” and focus on the “primary concepts, questionsand issues” (p. 52). In this analysis, the summary sheets captured salient information for eachparticipant across the four years to identify themes and patterns related to their perceptions ofthemselves as future engineers. All 40 semi-structured interviews were then coded using Atlas Ti software with open-codingstrategies. Open-coding strategies identify patterns and themes related to the research questionsthat arise inductively from data rather than through application of theory 40. This initial codingresulted in a long list of codes and associated definitions that grew with each successiveinterview analysis. To limit proliferation, the code list was refined by combining codes whenthey

Conference Session

Measurement Tools

Collection

2009 Annual Conference & Exposition

Authors

Lourdes Gazca, Universidad de las Americas, Puebla; Enrique Palou, Universidad de las Americas, Puebla; Aurelio López-Malo, Universidad de las Americas, Puebla; Juan Manuel Garibay, Universidad de las Americas, Puebla

Tagged Divisions

Educational Research and Methods

assignments.In addition, we encourage students to write brief reflective journal entries to further solidify andreinforce their own understanding, and demonstrate that improved understanding for animproved quiz grade.UDLAP’s Chemical, Civil, Computer, Electrical, Environmental, Food, Industrial, Mechanical,and Mechatronic engineering students have in EI-100 a great opportunity for a multidisciplinarycollaborative experience. EI-100 is a team-taught course that uses active, collaborative andcooperative learning, which has been a major player in UDLAP’s efforts of engineeringeducation reform since 200131. The major goal of the project “High-Quality Environments forTeaching and Learning Engineering Design: Using Tablet PCs and Guidelines from Research

Conference Session

New Learning Paradigms II

Collection

2009 Annual Conference & Exposition

Authors

Esat Alpay, Imperial College London; Peter Cutler, Imperial College London; Susan Eisenbach, Imperial College London; Anthony Field, Imperial College London

Tagged Divisions

Educational Research and Methods

ofsuch peer-based learning have been reported as: ≠ greater active and student-led involvement with the subject matter (Donelan and Wallace, 1998) ≠ lower student anxiety and higher student disclosure during tutorial work (Topping, 1998) ≠ improved subject dialogue within peer groups to support and enhance the feedback process and reflective learning (Nicol and Macfarlane-Dick, 2006), and possibly even overcome liminality when faced with a threshold concept (Meyer and Land, 2005) ≠ transferable, social and communication skills development (see e.g. Saunders (1992), Topping (1996, 2005), Maheady (1998) and Hirst et al. (2004)) ≠ improved student socialisation and enculturation within the

Conference Session

Modeling Student Data

Collection

2009 Annual Conference & Exposition

Authors

Mark Urban-Lurain, Michigan State University; Jon Sticklen, Michigan State University; Daina Briedis, Michigan State University; Neeraj Buch, Michigan State University; Thomas Wolff, Michigan State University

Tagged Divisions

Educational Research and Methods

Page 14.1295.10observational data that educational researchers routinely encounter and can be used in a varietyof settings to gain deeper insight into the factors affecting educational outcomes.AcknowledgementThis material is based upon work supported by the National Science Foundation under award0757020 (DUE). Any opinions, findings and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation (NSF).References1. National Science Board Science and Engineering Indicators 2002; NSB-02-1; National ScienceFoundation: Arlington, VA, April, 2002.2. Bernold, L. E.; Spurlin, J. E.; Anson, C. M., Understanding our students: A longitudinal

Conference Session

Modeling Student Data

Collection

2009 Annual Conference & Exposition

Authors

Micah Lande, Stanford University; Sarah Parikh, Stanford University; Sheri Sheppard, Stanford University; George Toye, Stanford University; Helen Chen, Stanford University; Krista Donaldson, Stanford University

Tagged Divisions

Educational Research and Methods

assigned to theIndividual Beliefs theme category tended to be more neutral. The number of responses sorted bytopic is generally even with an exception of the Teaching (Curriculum) topic, which had 324comments. For future work it could be useful to unpack this item into sub-groups for furtheranalysis.The School theme category topics are generally ordered with more negativity than the groupingof the Individual Belief theme category topics. It is interesting to note that both Co-op and Moneyare exceptions here. It may be that these two topics are much more concrete than the other moreabstract items or that, in reflection, the categorization of each should be reconsidered. In otherwords, finding benefit from experiencing a co-op experience and being

Conference Session

Classroom Engagement

Collection

2009 Annual Conference & Exposition

Authors

Dan Cernusca, Missouri University of Science and Technology; Ioan Gelu Ionas, University of Missouri Columbia; Harvest Collier, Missouri University of Science and Technology

Tagged Divisions

Educational Research and Methods

-351.9. Aleven, V., & Koedinger, K. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science, 26, 147-179.10. Chi, M. T. H., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improve understanding. Cognitive Science, 18(3), 439-477.11. Lin, X. D., & Lehmann, J. D. (1999). Supporting learning of variable control in a computer-based biology environment: Effects of prompting college students to reflect on their own thinking. Journal of Research in Science Teaching, 36, 837-858.12. VanLehn, K., Jones, R. M., & Chi, M. T. (1992). A model of self-explanation effect. Journal of the Learning

Conference Session

Engineering Design: Implementation and Evaluation

Collection

2009 Annual Conference & Exposition

Authors

Cameron Denson, Utah State University; Nathan Mentzer, Utah State University; Jodi Cullum, Utah State University

Tagged Divisions

Educational Research and Methods

conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect theviews of the National Science Foundation. References1. National Academy of Engineering, Changing the Conversation: Messages for Improving Public Understanding of Engineering. 2008, Washington, D.C.: The National Academies Press.2. Pearson, G. and A.T. Young, eds. Technically Speaking: Why All Americans Need to Know More About Technology. 2002, National Academy of Engineering.3. International Technology Education Association, Standards for Technological Literacy: Content for the Study of Technology. 2000, Reston, VA: Author.4. National Center for

Conference Session

Knowing Our Students, Faculty, and Profession

Collection

2009 Annual Conference & Exposition

Authors

Marisa Orr, Clemson University; Zahra Hazari, Clemson University; Philip Sadler, Science Education Department, Harvard-Smithsonian Center for Astrophysics; Gerhard Sonnert, Science Education Department, Harvard-Smithsonian Center for Astrophysics

Tagged Divisions

Educational Research and Methods

order to examine the relationship between outcomeexpectations and occupational preference in more depth, the detail provided by Vroom’sExpectancy Theory3, specifically the valence model, is useful.Social Cognitive Career Theory2 can be used as a lens through which to examine which types ofoutcome expectations women and men have about an engineering career. According toBandura’s social cognitive theory4, outcome expectations are the anticipated consequences of acourse of action and can be physical, social, or self-evaluative. For example, a student mightexpect that the outcome of earning an engineering degree will be making money (physical),becoming well-known (social), or developing new knowledge (self-reflective). Lent, Brown,and Hackett used

Conference Session

Measurement Tools

Collection

2009 Annual Conference & Exposition

Authors

Heidi Diefes-Dux, Purdue University; Matthew Verleger, Purdue University; Judith Zawojewski, Illinois Institute of Technology; Margret Hjalmarson, George Mason University

Tagged Divisions

Educational Research and Methods

reflect engineering practice. High quality andreliable feedback and assessment strategies must accompany these learning experiences to ensurethat student learning is achieved (e.g. misconceptions are addressed) and the quality of studentwork increasingly reflects what is valued in engineering practice.Model-Eliciting Activities (MEAs) are one instructional approach to developing these and othercompetencies3,4. These client-driven, open-ended, team-oriented problems have beenimplemented in a large (N = 1200-1600) required first-year engineering problem solving andcomputer tools course since Fall 20025,6. Over 20 different MEAs have been implemented and anumber of feedback and assessment strategies have been employed with varying degrees ofsuccess6

Conference Session

ERM Poster Session

Collection

2009 Annual Conference & Exposition

Authors

Stephen Snyder, Taylor University; Elise Romines, Taylor University; Rachel Dodge, Taylor University; Jason Kruegar, Taylor University; Travis Booth, Taylor University; Josh Gates, Taylor University

Tagged Divisions

Educational Research and Methods

structure, knowledge is gained by support, participation and nurturingwith others17,18. These areas of motivation were assessed because of their strong connection toachievement, spending time on complex activities, learning and growth goals, the use of deeperand more reflective strategies for learning, more risk taking and the focus on the learningprocess21.Valuing Science It is a goal of the HARP program for students to learn to value science education,discovery and future careers in science. This goal will be assessed specifically by measuring theincrease in students valuing the problem solving process, the calibration process, the scientificmethod in application to real life problems, documenting for repeatability, data analysis

Conference Session

Using Classroom Technologies

Collection

2009 Annual Conference & Exposition

Authors

Joanna Garner, Pennsylvania State University; Allen Gaudelli, Pennsylvania State University; Sarah Zappe, Pennsylvania State University; Michael Alley, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

the research on learning and multimedia presentationdesign, which emphasizes the importance of providing images that promote integration betweenconcepts. Not reflected in Table 3 are the decorative images from the use of PowerPoint defaultbackgrounds, such as those shown in Figure 5. In our survey, we determined that 47% of theslide sets examined of slides used such a background. As asserted by Carney and Levin,19 suchdecorative images slightly reduce the comprehension by audiences.Table 3. Common practice statistics on image level.Classification Definition StatisticsDecorates Not relevant to text 5%Partially Represents

Conference Session

Classroom Engagement

Collection

2009 Annual Conference & Exposition

Authors

Sarah Zappe, Pennsylvania State University; Robert Leicht, Pennsylvania State University; John Messner, Pennsylvania State University; Thomas Litzinger, Pennsylvania State University; Hyeon Woo Lee, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

the videos in order tolearn the material necessary to be successful in the quizzes. This helps to assure that studentswill be prepared for the in-class activities. Second, the instructor can use the results of thequizzes as a launching point for discussion and adjust the class plan as necessary to address anystudent misconceptions or lack of understanding, in a form of just-in-time teaching. 8The classroom flip method may be perceived to be particularly beneficial to students who prefercertain types of learning environments. According to the Felder-Solomon Learning Styles Index,students may classify themselves along four dimensions as being a certain type of learner:active/reflective, sensing/intuitive, visual/verbal, and sequential/global

Conference Session

Educational Research

Collection

2009 Annual Conference & Exposition

Authors

Richard Layton, Rose-Hulman Institute of Technology; Susan Lord, University of San Diego; Matthew Ohland, Purdue University

Tagged Divisions

Educational Research and Methods

consider new ways to thinkabout our data. As Tufte says, “if displays of data are to be truthful and revealing, then the logicof the display design must reflect the logic of analysis”.5 Multiway plots assist us in extractingthe story the data tell. Page 14.1009.4Method and results: transforming column charts to multiway plotsEighth-semester persistence data. To interpret multiway plots in contexts that speak toengineering education audiences, we use categorical data from MIDFIELD (the Multiple-Institution Database for Investigating Engineering Longitudinal Development) on eighthsemester persistence disaggregated by race and gender. MIDFIELD data

Conference Session

Modeling Student Data

Collection

2009 Annual Conference & Exposition

Authors

Isaac Wait, Marshall University; Andrew Nichols, Marshall University

Tagged Divisions

Educational Research and Methods

and non-attendees with TOEFL score < 540, and differences wereanalyzed by two-way crosstabulation (chi-squared analysis).Of the five learning activities, females indicated significantly higher rates of printing notesprovided by the instructor (73.6% of females, compared to 62.3% of males; p=0.03) and takingtheir own handwritten notes during class lectures (81.1% of females, compared to 67.6% ofmales; p<0.01). These elevated study habit tendencies may be reflections of the core reasons thatfemale students experience greater academic achievement than male students. Differencesbetween male and female students in attending class lectures, working together with otherstudents on homework assignments, and reading textbooks were not

Conference Session

Knowing Our Students, Faculty, and Profession

Collection

2009 Annual Conference & Exposition

Authors

Kevin Anderson, University of Wisconsin, Madison; Sandra Courter, University of Wisconsin, Madison; Thomas McGlamery, University of Wisconsin, Madison; Traci Nathans-Kelly, University of Wisconsin, Madison; Christine Nicometo, University of Wisconsin, Madison

Tagged Divisions

Educational Research and Methods

process. Arguably, this process is a large part of engineering, but it’s not the whole picture.≠ Bailey and Gainsberg: One limitation of this study is that it does not encourage engineers to significantly reflect on their practice and why they do certain things, it is more objective. The voice of engineers does not significantly appear to factor in. The study does not aim to suggest improvements to the education of engineers; it simply reports that engineers learn some things in a university setting and some through practice. It does not question those norms.≠ Collin’s work is mainly limited in scope, just considering workplace learning in Finland.≠ A limitation of the study of Korte, et al., is that it just focused on new engineers. It did use