. Page 11.1112.1© American Society for Engineering Education, 2006 Self-Efficacy Beliefs of First-Year Engineering Students: In Their Own WordsAbstract Numerous studies have used quantitative self-efficacy measures to predict the choices,achievement, and interests of undergraduate engineering students. Self-efficacy theorists,however, argue that a discovery-oriented, qualitative approach is required to better understandthe sources and cognitive processing of students’ self-efficacy beliefs - their beliefs about theirabilities to complete the tasks that they deem necessary to achieve a desired outcome. This studyhas therefore employed qualitative measures to investigate the self-efficacy beliefs
2006-1812: WHAT AFFECTS STUDENT SELF-EFFICACY IN AN HONORSFIRST-YEAR ENGINEERING COURSE?Melissa Sumpter, Purdue University Melissa Sumpter is an undergraduate student in the Department of Management at Purdue University who is pursuing minors in both Chemistry and Marketing. She is a member of the national chemistry fraternity, Alpha Chi Sigma. Her research interests are focused mainly on engineering education. Her research is directed by Dr. George M. Bodner, Dr. Deborah K. Follman, and Mica A. Hutchison.Deborah Follman, Purdue University Deborah Follman is an Assistant Professor in the Department of Engineering Education at Purdue University. She received a B.S. in Chemical
scale measuredthe extent to which students believed that their academic performance was dependent on factorsthey controlled, such as the amount of their study or effort (e.g., ‘‘If I try hard enough, then I willunderstand the course material’’). The eight items of the self-efficacy scale measured the extentto which students believed that they were competent in terms of task-related abilities and skillsand had a high likelihood of a successful academic performance (e.g., ‘‘Considering thedifficulty of this course, the teacher, and my skills, I think I will do well in this class’’). The fiveitems of the test anxiety scale assessed the extent to which students experienced discomfort orhad negative thoughts that could interfere with their test
knowledge.Second, we examined student self-efficacy, defined as a personal judgment of one’s capability toperform a particular activity1, a construct that has been positively linked to motivation andacademic performance3,9. Because these learning measures are task-specific, the questionnairesand rubrics we developed for their assessment are important research outcomes.We used a repeated measures (pre-post) experimental design, with experimental and controlconditions to compare student learning of core topics taught with and without the Oracle-basedmodule. Comparisons suggest that inclusion of the Oracle-based exercises not only did notdetract from functional learning, but also increased self-efficacy about technology.In the next section, we provide a
, and Waggoner26 conducted at a well-established Midwesternuniversity, the math test scores of females in both engineering and biological sciences wereexamined. Also, to determine if confidence differed by major, confidence scales wereadministered to the same females entering both programs. In essence, the females majoring inengineering had both higher math entrance scores and stronger measures of self-confidence thantheir female counterparts in biological sciences.However, when comparing women to men, several studies have found that women self-reporttheir academic confidence and engineering self-efficacy as lower than men's.2,4,5,28,29Accordingly, self-efficacy may be enhanced or diminished due to feedback from external factorssuch as society
takendirectly from the General Self-Efficacy Scale (GSE) developed by Jerusalem and Schwarzer18.The researcher adapted five questions for self-confidence from the Women in EngineeringPrograms and Advocates Network (WEPAN) Student Experience Survey19. Table 2 shows themeasures and the survey questions related to each measure.Each measure was based on Likert scale and/or personal/demographic questions. The sevenlevels of the Likert scale were: 1 = Strongly Agree (SA), 2 = Disagree (D), 3 = Mildly disagree(MD), 4 = Neither agree nor disagree (N), 5 = Mildly agree (MA), 6 = Agree (A), and 7 =Strongly agree (SA).Table 2Measures and the Related Questions Measures Questions Self-Confidence
engineering has been disputed in the literature. To provide furtherdata to answer this question, portions of the Purdue Spatial Visualization Test (PSVT)were administered to freshman engineering and undeclared students from a College ofEngineering and Physical Science (CEPS). In addition, a self efficacy test, which wasdeveloped to assess the self confidence of students related to spatial tasks, was alsoadministered. The data analysis showed that those students who remained in CEPS fromtheir freshman to sophomore year (either change majors within CEPS or stayed in thesame major) performed better on the PSVT than those students who changed colleges orwithdrew from the university. For the self efficacy measure, a similar effect was found;however, this
, and skills35, the twoconstructs are empirically distinct. With the shift to team-based work in many organizations,researchers have established that group efficacy is a meaningful and measurable groupattribute34, 36-37. In fact, a recent meta-analysis of 67 empirical studies found that collectiveefficacy had a positive relationship with performance (p=0.41; reference 37). Although self-efficacy has been studied with regard to gender issues in an engineering context (e.g., references38-39), less attention has been given to the construct of collective efficacy. In addition, tolerancefor ambiguity and efficacy relation has not been investigated in an engineering design context
2006-1354: THE CHEMICAL ENGINEERING ENVIRONMENT: CATALYST ORINHIBITOR TO STUDENTS' CONFIDENCE IN SUCCESS?Deborah Follman, Purdue University Deborah K. Follman is an Assistant Professor in the Department of Engineering Education at Purdue University. She received a B.S. in Chemical Engineering from Cornell University in 1994 and a Ph.D. in Chemical Engineering from North Carolina State University in 2000. Her research interests include engineering education and gender equity, specifically regarding self-efficacy, issues of gender on student cooperative learning teams, and curriculum development.George Bodner, Purdue University George M. Bodner is the Arthur E. Kelly Professor of Chemistry, Education
errors for elementary mechanics The frequency of common errors decreased for all except error 2b; therefore theresults appear to confirm expectations that as students spend more time creativelyconstructing their own problems, their problem-solving skills improve. Since it is alsotrue that the extra time is the controlling factor for the change, we also explored theimprovements in terms of students’ self efficacy beliefs.9-10 Bandura11 defines this self-efficacy as students’ perception of their capability to accomplish a desired task.Moreover, self-efficacy is important since it influences the course of action studentschoose to pursue in their efforts to build problem-solving skills— how long theypersevere in facing obstacles and their
affective measures related to increased interest in andawareness of careers related to photonics or other STEM fields. We were particularly focused on Page 11.1055.11reaching underrepresented ethnic/cultural groups and females. Research suggests that the barriersto greater involvement in STEM careers for underrepresented minority groups and women arestrongly related to factors such as people’s beliefs about their competence in the science-relatedareas2,3,6. Specifically, low self-efficacy beliefs, lack of encouragement, and a lack of access tomaterials and resources together with other cultural, familial, and socioeconomic factors conspireto keep
“moderate,” 61 to 80 to “frequent,” and over 80 to “intense” feelings. Though both self-efficacy and IP account for a great number of studies in education andpsychology, we are unaware of any studies that have looked at both simultaneously.Interestingly, many of the factors measured by Clance’s scale suggest strong ties to self-efficacytheory. Feelings that successes cannot be repeated, for example, may be tied to students’assessments of their mastery experiences when they are forming their efficacy beliefs. Inaddition, students’ comparisons of their capabilities to those of their peers are vicariousexperiences which are also significantly influential on efficacy beliefs. In the case of an IPsufferer, the negative feelings associated with
thisproject, as one of the goals of this project is to demonstrate to students all of the benefits thatwill accrue to those who learn about technology.Self-Efficacy: Self-efficacy measures students’ beliefs about their ability to achieve onschool-learning tasks. If students feel competent and empowered to succeed in school, theywill have high scores on self-efficacy. This measure also is particularly important for thisproject, as one of the goals is to increase students’ belief that science and technology learningare tasks that they can complete. This will be particularly important to students in this class,as many of them will be elementary school teachers. If the preservice teachers can develop asense of technological self-efficacy, they can
withthe PIE program… [Her] grades improved a lot this marking period and we feel that PIE actuallyhelped her to achieve better grades…”Leadership opportunities, self-esteem, self-efficacy. By its very nature, the PIE program forceseach of the mentors to take on a leadership role. This is particularly valuable for PIE mentorswho had not previously held a leadership position at Clarkson (e.g., 4 in AY02). Mentors haveprovided variable responses regarding the program’s impact on their self-esteem and self-confidence and have generally reported having a high level of self-esteem at the start of theprogram. Self-efficacy, which is a measure of a person’s confidence in her ability to take action,is closely related to self confidence. Mentors have
. Page 11.632.9Variable 4: Amount of Computer Use The connection between computer use and positive attitudes and interest has been amplysupported by previous research15, 38. While experience with computers games has been shown tobe an important predictor of men’s interest in computer related fields40, this is not the case forour women respondents. Other research has shown, however, that experience with computerprogramming may be an important predictor of self-efficacy and success in a computer field forwomen. Learning a programming language is significantly associated for women with anincreased sense of computer competence28, 42. High school programming experience has alsobeen shown to be a significant predictor of women’s success in
Page 11.1404.9identified psychological processes (self-efficacy, approach/avoidance behavior, and locus ofcontrol) that facilitate a student’s decision to stay in college or leave, many of which arereflected in these essays. Additionally, some differences were noted between the LLC Teniwestudents themselves and appeared to be aligned by their major. Finally, the essays were minedfor information regarding the students’ perceptions of the LLC program and in essence provideda “student evaluation” for the program.Seminar group 1 summary Common student goals for the year included making friends and getting good grades.Many students felt they had benefited from common living arrangements and campus resourcesprovided by the LLC. Other common
interdisciplinary teams1, 2. As a result, many engineeringprograms now devote a portion of their curriculum to team experiences and buildingcommunication skills. These activities are designed not only to equip students with theinterpersonal skills that they will need in their career, but to build self-efficacy and helpincrease retention3.The Engage program at the University of Tennessee was designed to be an integratedcurriculum that would “continue to teach essential skills, using techniques that improveproblem-solving ability, teach design methodology, and teach teamwork andcommunication skills,”4. The Engage program is a 12 credit hour, two-semester coursethat all first year students are required to take. The program was piloted in the 1997-1998academic
Education. 21:5, 491-508.12. Edwards, H. (1993). Mistakes and Other Classroom Techniques: An Application of Social Learning Theory. Journal of Excellence in College Teaching. 4, 49-60.13. Goodwin, S. (1997). The Effects of Error Detection Instruction on Developmental Algebra Students. Dissertation. West Virginia University.14. Socha, D., Razmov, V., and Davis, E. (2003). Teaching Reflective Skills in an Engineering Course. Proceedings of he 2003 American Society of Engineering Education Annual Conference and Exposition.15. Lorenzet, S., Salas, E. and Tannenbaurm, S. (2005). Benefiting from Mistakes: The Impact of Guided Errors on Learning, Performance and Self-Efficacy. Human Resource Development Quarterly. 16:3, 301
. There are many activities in collegebesides academics such as sports, parties, and social life in general. These extracurricular(social) activities may come in the way of students’ academic work and jeopardize theirperformance. However, according to research on self-regulated learning, students who exerciseself-regulated learning strategies in the midst of all distractions are more likely to succeed intheir academic endeavors. 13Four items in the instrument assessed classroom engagement. These items dealt with doinghomework, assignment completion prior to class, studying, and taking notes in class.Self-regulated learning was assessed with self-regulated learning subscale from Bandura’sMultidimensional Scales of Perceived Self-Efficacy developed
minor werephrased as questions in a recent assessment of the program:281. How does the minor affect students’ motivation and self-efficacy?2. Are these students more successful in tackling ambiguous problems and thinking innovatively?3. Are these students more likely to see the connections to aspects of problems outside those related to their individual discipline, especially relating to business and finance?4. Do these students exhibit better communication, leadership, and teamwork skills?This study28 of existing student attitudes found: • While there were statistical trends that the students in the minor had a higher self- efficacy, no definitive statements could be made regarding this difficult to measure
+/- one standard deviation of each other and of the National averages.Interestingly, unlike the Science scores, which showed a mixture of student affinity relative tostudent confidence levels, Figure 3 shows that at every school – as well as the national averagedata – students responded more positively to questions regarding their confidence in mathematicsthan to questions concerning how much they like the subject.Given that quantitative survey response methods fall short of adequately assessing our program’simpact on student attitudes or feelings of self-efficacy, other than to show that our students’attitudes are in line with the National averages, we’ve used post-program questionnaireresponses and reflective essays to provide additional
computer skills level, perceived self-efficacy for using advanced instructional technologies in the classroom, and level of agreement with statements about conditions and policies at the state and local level. In profiling the system over time, we have used four traffic data points to capture incremental growth. Thus, we use these observations primarily as descriptive statistics – a way of determining where we are at any given time. • Cumulative Total Hits: a cumulative measure of traffic for PRISM (the time frame starts on 1 October 2003, the point at which the system had been open to the public for less than a month). • Cumulative Average # Hits per Day: while a good indictor of trends
XSr. Exit Confidence in S 8 X X X X XknowledgeSr. Exit Self efficacy S 7 X X X XFor each of the rubrics developed for assessing Senior Design artifacts, therelevant program outcomes are identified. An example (Table 2) is the allocationof rubric elements to program outcomes for the assessment of the final writtenreport. This is the most detailed rubric used in the course and illustrates that eachoutcome is assessed in multiple sections of the rubric. Table 2 Outcome assessments allocated to elements of final written report rubric.Rubric element Points a
the students for use as thebasis for a section of their final project reports subtitled “Constraint Considerations andRamifications.” Along with this, the grading rubric distributed in the syllabus wasmodified to evaluate how well this is accomplished by each project team. During Fallsemester 2005, Dr. Min was invited to read students’ impact statements regarding socialconstraints, and to offer opinion about their ability to synthesize global enterpriseconcepts with their company-specific projects.Assessment improvements have been made in several ways in IE 441. A pre- and post-test was designed and administered to IE 441 students the first and last days of the Fall2005 semester. The test indicates their current knowledge and self-efficacy
patterns. Using the facilities Page 11.183.5available at the Advanced Transportation Engineering Systems Laboratory, the teacher was thentrained on the use of VISSIM traffic simulation software, and conducted simulation studies forthe previously selected sites to evaluate their operational performance under the existing andfuture traffic conditions. The teacher identified existing and potential traffic problems byanalyzing the results obtained from both the HCM-based and VISSIM simulators, in terms of“measure of effectiveness” estimation, and recommend possible improvements for HCM models. A field trip connected with each research project