trainingAbstractThe case study described in this paper was a formative evaluation on the adapted schema trainingmodules and materials. The study was intended to gather feedback and suggestions from theintended audience in order to revise the training modules. The study also assessed students’overall experiences and performance regarding the tryout of the modules. Both qualitative andquantitative data were collected from the participants. Based on the case of four participants, (1)the training materials were well adapted for undergraduate engineering students; (2) the trainingmodels were effective, (3) the training modules would be more effective for students with lesscoursework in the engineering subjects covered by the modules.Introduction and
Bandura’s theory to explain the development of career interests, choices, andperformance. According to their Social Cognitive Career Choice Model, shown in Figure 1,person inputs, such as gender, affect outcome expectations through learning experiences.Outcome expectations in turn have both direct and indirect effects on choice goals. In this Page 14.306.2context, a choice goal is the occupation that a person chooses to pursue, which leads to choiceactions, such as enrolling in an appropriate program for the chosen profession. Self-efficacy alsoplays a large role in the development of outcome expectations, interests, choice goals, choiceactions, and
problem solving, some researchers within the mathematics education communityhave advocated for combining cognitive and situative approaches to account for the social andmaterial context a problem solver acts in. Greeno and his colleagues suggest that this isparticularly appropriate when considering groups of people or “intact activity systems”, whilethe cognitive perspective focuses on individuals5. We thus integrate social resources andmaterial resources into the framework , as influenced by McGinn and Boote’s discussion ontheir study of mathematical thinking6. The five aspects of mathematical thinking investigatedin this study are presented in Table 1.For this study, we examine how designers engage in mathematical thinking while
exercisestargeted to the course level were open-ended problem-solving assignments with no clear-cut “right” answer or approach, and written assignments with a reflective component,frequently requiring judgment in the face of uncertainty. Table 1, taken from thisprevious study, summarizes the relationship between the steps of problem solving4 andthe components of a complete act of thought as proposed by Dewey5. Dewey’s workforms the foundation for current literature on critical thinking.Problem Solving Complete Act of Thought1. Define the problem (i) a felt difficulty (ii) its location and definition2. Explore a variety of solutions (iii) suggestion of
“Excellent,” 16% were “Good,” <1% were “Average,”and none were “Fair” or “Poor.” As gratifying as this level of participant satisfaction is, however,it provides no real indication of what the workshop has actually accomplished. In the spring of2008, we designed and administered a survey to all of the NETI participants in the 1993–2006offerings whose contact information we could find. The survey—hereafter referred to as theNETI Alumni Survey—is shown in Appendix B. It asks the participants about their teachingpractices, their students’ and their own ratings of their teaching, the effects of the NETI on boththeir practices and their ratings, their involvement in educational research and instructionaldevelopment, and several demographic questions
content. Studentswere open to the use of the recorded lectures, as supported by preliminary assessment datashown in Figure 1. The instructor of the course wanted to take the next step and flip the coursefor a variety of reasons. First, the availability of online lectures would allow students to beexposed to theory-based content outside of class time. Taking the lecture out of class wouldallow greater time for in-class problem solving and increase the opportunity for increasedteacher-student interaction. In addition, the use of the practicum period, which had previouslybeen used to deliver course content, could be used for students to work on group projects, withthe instructor available for assistance and guidance. Figure 1: Feedback
is toexamine how critical thinking actually occurs in practice. It is driven by the following tworesearch questions: 1. What are the processes students use to solve critical thinking problems? 2. What do students believe that critical thinking is?These questions are examined within the context of the theoretical framework of Mason. Asdescribed above there are a number of conceptualizations of critical thinking, each of whichemphasizes a different aspect. Mason1 has synthesized these different aspects into an overallconceptual framework. The components of his framework are (pp. 343-344): ≠ The skills of critical reasoning (such as the ability to assess reasons properly; ≠ A disposition, in the sense of: o A critical
literature. Thispaper details the results of the quest to find support for the STATEMENT. This is not the firstinvestigation into the source of these numbers, as a literature search reveals that Molendaessentially debunked these numbers in 2004 1.The STATEMENT in LiteratureIn this section, some of the sources of the STATEMENT are examined as well as a brief genealogy Page 14.1274.2depicting its propagation through archival literature. The first occurrence of the STATEMENTseems to appear in a 1967 trade magazine article 2 by Treichler, who was affiliated with theSocony-Vacuum Oil Co. (note that Socony is an abbreviation for Standard Oil Company of NewYork
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of action for a givendomain-specific task.[1, 2] An individual’s self-efficacy plays a crucial role in theirability to conduct a particular task; however, self-efficacy toward engineeringconcepts is rarely analyzed. Information about engineering student levels of self-efficacy on engineering tasks can be useful for educators to plan and structureengineering courses.The following paper describes an exploratory pilot study conducted to inform thedevelopment of an instrument designed to identify self-efficacy towardengineering design. Engineering design, or the process used to devise a system,component, or process to meet a desired need, was chosen as the focus because ofits importance in the field of engineering.[3]Instrument development was
workplace, engineering educators must betterunderstand the current work and values of professional engineers. However, formal research inthis area is limited. In this portion of our study we interviewed practicing engineers (n=45),surveyed engineers, engineering managers and individuals with engineering backgrounds(n=280), and conducted a case study of one engineering firm. In order to better understand theepistemic frame of engineering, or what makes an engineer an engineer, this study used agrounded theory approach. This approach used the viewpoint of engineers to uncoverimplications for engineering education. We gained insights on (1) what engineers see as notableand as exemplifying engineering in their work, (2) what aspects of their work they
, and their willingness to administer the surveys college-wide. Tests of validity andreliability were conducted on both instruments. The instruments were then refined and shortenedbased on the psychometric properties of the items in the original instruments.Ultimately, we hope to make the instruments available to the national engineering educationcommunity so that they might improve the ways in which they teach tomorrow’s engineers. Thispaper will discuss the ongoing progress of both instruments as well as summarize resultsobtained from their administration.IntroductionEngagement has no universally accepted definition, although several researchers haveoperationalized it in many different ways. Chen, Lattuca, and Hamilton [1] defined
determined the accuracy with which subjects perform the tasks. In order ofdecreasing accuracy, these perceptual tasks are (as summarized by Robbins2): 1. Position along a common scale 2. Position along identical, nonaligned scales 3. Length 4. Angle or slope 5. Area 6. Volume 7. Color hue, color saturation, densityThis list helps us identify the problems associated with bar (and column) charts. Horizontal bars(or vertical columns) define areas on a graph, and the list shows that our perceptions of area areless accurate than our perception of other graphical elements. Moreover, the area of a barcontains no data—often only the endpoint of the bar represents data. The area of the bar just getsin the way of our ability to make
) Page 14.1290.3and faculty assistance. The learning objectives included developing problem solving techniques,improving communication, working in teams, understanding time management, understandingthe impact of problem resolution, understanding the relatedness of multiple engineeringdisciplines, and developing an appreciation of the courses in their engineering curriculum. Weused a multi-tiered undergraduate research approach which incorporated student advising andmentorship, weekly individual meetings (15-30 minutes), a group meeting (1 hour), reportwriting, and participation in national or local research conferences.The students were supervised by the CBE committee in conducting scientific research in theareas of biosensors and bioelectronics
atMissouri University of Science and Technology. The principal conclusion is that it is imperativeto the success of this type of program to provide a mechanism for frequently collecting feedbackin order to prioritize and schedule activities to best meet the needs of participants.IntroductionThe National Science Foundation (NSF)-funded project “A Program to Facilitate ScholasticAchievement in Computer Science, Engineering, and Mathematics” at Missouri University ofScience and Technology (Missouri S&T) ran from August 15, 2004 through July 31, 2009. Thegoals of this program were to address: (1) the decline in the number of students pursuing degreesin mathematics, computer science, and engineering, and (2) the minimal rate of low-incomestudents
were not part of the pilot group. In addition thereport presents similar performance analysis from collaborating institutions – HoustonCommunity College and TAMU Corpus Christi. I. MotivationThe College of Technology – Computer Engineering Technology (CoT – CET) program at theUniversity of Houston has implemented an undergraduate peer mentoring model as part of anNSF-sponsored program (grant no. DUE 0737526) examining the impact of incorporatingconcept mapping and undergraduate mentors on student learning at the freshman and sophomorelevels. The training for this mentoring model has been adapted from a peer-led team learningprogram [1] and incorporates concept mapping as a primary pedagogical tool for increasingmentee understanding of key
average environmental knowledgescores. There is no difference in average knowledge scores when comparing male and femalestudents. In addition, we report the results of an analysis of students’ data as collected within theworkshops. The study reveals several areas of troublesome knowledge of students. Page 14.1088.2IntroductionIn its report entitled “The Engineer of 2020: Visions of Engineering in the New Century”, theNational Academy of Engineering (2004) reported by the year 2020 “the world’s population willapproach 8 billion people”1. Not only will urban areas and developing nations experiencesignificant increases in population centers
the casesbring us the following questions: (1) What makes engineering students cheat on their writing?(2) What types of plagiarisms are happened in engineering classroom? and (3) How doinstructors in engineering educate their students to prevent plagiarism? In order to answer thequestions in this paper, we investigate and discuss the plagiarism issues in engineering program.For the first step of this research, we investigate the types of plagiarism that frequently happen inengineering classes. Then, we select ‘plagiarism in writing’ for our further investigation amongvarious types of plagiarism, since this is the most frequent and serious one in engineeringclasses. The second step is to adapt an anti-plagiarism tool to the classes. Among
-going program of researchdesigned to better understand the major difficulties that students encounter as they learn todevelop and apply models to solve Statics problems. In the first phase of this research,1 morethan 300 students completed three inventories - math skills, spatial reasoning and statics concepts.The results from the inventories were used to identify clusters of students with commoncharacteristics, and therefore, presumably common deficiencies in their problem-solving inStatics. Students from each cluster were invited to participate in think-aloud problem-solvingsessions to identify the weaknesses in their problem-solving. Although the think-aloud analysesdid not reveal differences among the clusters of students, it did uncover
skills.The project described in this paper is the initial stage of the multi-year study in which we visitedten engineering programs and collected data which will inform the development of a nationalsurvey to be administered in the spring of 2010. Although the overall study is only in its secondyear, the data collected in the first year provide us with both a platform upon which to build thenational survey and cultural context which will inform analysis of the survey data. Page 14.189.3Hypothesis Figure 1: The Determinants of Ethical Development As shown in
points for a correct solution missing thesteps used to arrive at the solution, and 5 points for either not showing units or the correctnumber of significant figures. Key attributes of each course are presented in Table 1. Ofparticular note is the relatively large number of homework assignments per term for eachcourse: homework clearly represents a significant load on students and faculty. ENGR 20 CIVL 130 CIVL 133 EMGT 170Number of sections in study 4 6 6 8Total number of students 108 185 74 168Average number of students per section 27 31 12 21Average
Research, Review of Educational Research, Review of Higher Education,Studies in Higher Education).Inclusion CriteriaEach article chosen for inclusion in the database was determined by us to meet all five of thefollowing criteria: 1. It had an educational intervention. 2. The intervention was at the undergraduate level. 3. The intervention was in a science, technology, engineering, or mathematics (STEM) field. 4. It discussed an outcome (no matter how anecdotal). 5. The outcome was related to improved learning or performance, retention, or assessment (and not simply student satisfaction).Although we have classified all the articles accepted for inclusion as “research,” this does notnecessarily reflect
solving and algorithmic thinking before introducing syntax. Intraditional first year courses, students must master algorithmic thinking and syntax simultaneously. Byusing a drag and drop editor in the Alice software, students are freed from the difficulties of syntax errors,such as missing commas or semicolons, allowing them to focus on problem solving and algorithmicthinking. Early on in the curriculum, the concept of object oriented programming is introduced.1 A featureof the Alice software is the use of three dimensional graphics (3D) to create virtual worlds. Using theAlice software, students may test their programs in 3D virtual worlds, an environment that has greatappeal to a generation of students that grew up in a multimedia environment
assess and evaluate the effects of innovation on a student’s entire engineering education. PCM addresses many topics outlined by the Educational Research and Methods Division (ERM) including active and cooperative learning, integrated and non- traditional curricula, life-long learning, new learning models and applications, and the art and science of teaching. This paper explains PCM and how it relates to engineering education, analyzes selected ASEE presentations in relationship to the four parallels, and illustrates how PCM integrates key curriculum components and the four interrelated parallels to create innovative curricular designs in engineering education.1 Introduction1.1
, over five years later, thereremains a wide variability in outcome assessment strategies employed by various professors).This prompted the author to embark on an empirical study of course-specific outcomeassessment strategies, the results of which are summarized in this paper.The basic questions addressed in this study include:1. formulation of content-specific learning outcomes that can be consistently and quantitatively assessed;2. formulation of effective outcome assessment instruments along with mechanisms to determine outcome demonstration thresholds;3. formulation of grading strategies that incorporate outcome demonstration thresholds yet produce results consistent with prior (accepted) grading practices; and
employed specific implementations of these elements, broadercharacteristics of these elements emerged. First, the challenging project necessitated the practiceof team processes and provided strong motivation. Second, effective teamwork processesexhibited the characteristics of direct applicability to team goals and appropriate investment ofeffort for returned value. Third, accountability with coaching appeared to be a strongcombination to keep students’ behavior professional and to keep teams on track with the project.1. IntroductionStudent teams are commonly used to teach design skills side-by-side with teamwork skills. Ourexperience with these classes is that while many teams produce excellent results other teamsunravel. On the low performing
, using a questionnaire methodology: i) Do engineering studentsbecome more active and metacognitive readers between their freshman and senior years;ii) do engineering students become less “transmission” oriented and more “transaction”oriented in their beliefs about text? The results are considered in terms of theirconsistency with other available data about engineering students’ study behaviors, and interms of implications for the design of undergraduate engineering curricula.IntroductionThe claim that “Engineering is a profoundly creative process”1 seems entirely correct as adescription of the nature of professional engineering. It also conveys a sense of themindset and skill levels that are set as goals for advanced students in engineering
the strategic and meta-cognitive processes that learners use to integrate multiple representations and acquire knowledge that will transfer and be useful in problem solving. She can be contacted at pnv1@psu.edu. Page 11.15.1© American Society for Engineering Education, 2006 A Cognitive Study of Modeling during Problem-solving: An integrated problem solving modelIntroductionA fundamental issue in engineering education is the question of how to improve students’analytical skills.1 Analysis skills are central to engineering students’ abilities to interpret andsolve problems and the