(strongly agree). The instrument is scored by simple summationof student responses. Scores on the individual scales and subscales should be compared to themaximum possible score, which is seven times the number of items in the scale. All items, broken downby scale and subscale, are listed in the Appendix.The 2014 Standards for Educational and Psychological Measurement (AERA, APA, & NCME, 2014) wereused as a framework for gathering evidence of validity for the self-efficacy instrument, following thevalidation process presented by Cook (2016). A summary of validity evidence used is presented in Table1 and discussed in detail below. Table 1: Evidence of validity, definitions from Cook (2016, p3) Type of Evidence Definition
sensing.” Journal of NeuroEngineering and Rehabilitation. 2(4), 1-7.8. Berzowska J. (2005). “Electronic Textiles: Wearable Computers, Reactive Fashion, and Soft Computation.” Textile. 3(1), 2-19.9. Lam Po Tang, S. (2007). “Recent developments in flexible wearable electronics for monitoring applications.” Transactions of the Institute of Measurement and Control, 29 (3-4), 283-300.10. Raelin, J. A., Bailey, M. B., Hamann, J., Pendleton, L. K., Raelin, J. D., Reisberg, R., and Whitman, D. (2011). “The Effect of Cooperative Education on Change in Self-Efficacy among Undergraduate Students: Introducing Work Self-Efficacy.” Journal of Cooperative Education and Internships. 45(2), 17-35.11. Chubin, D. E., May, G. S., and
for their own learning, is ideally suitedfor supporting the development of metacognitive self-regulation23,35,36. In this study, we definedmetacognitive self-regulation as pre-service teachers’ ability to apply specific learning strategiesto plan, monitor, and evaluate their learning while solving real-world problems.MethodThis pilot study was conducted during the spring 2011 semester as an observational case study37,38, 39. Quantitative and qualitative measures were applied to better understand how and in whatways does engagement with the STEM PBL Challenges affect pre-service TEE students’ (1)knowledge of PBL pedagogy, (2) critical thinking skills and metacognitive self-regulation, and(3) motivation and self-efficacy for applying PBL
, motivation,and retention rates over time, and examine differences as a result of participating in LTS experi-ences. Self-efficacy and motivation will be evaluated through a survey based on a recent modelfor engineering design self-efficacy18. As the evaluation is performed repeatedly over the three-year project duration, we will have the ability to measure retention in engineering disciplines anduniversity education over time. We will pay particular attention to those underrepresented in en-gineering (i.e., women and minorities). As a summative measure of these indicators, graduatingstudents will also be surveyed for graduation rates (by the fifth year of academic study) and post-baccalaureate activity (e.g. employment, graduate school, type of
research article. Outcomes aremeasured at every end-of-semester. The generated data allow for evaluating the efficacy ofUSTEM2 versus USTEM1 and the parametric characterization of trends across semesters. In thisreport, we present preliminary results generated from five completed measurement occasions (M1-M5) for Cohort 1 (at M1: USTEM1, n=22; USTEM2, n=19) and Cohort 2 (at M1: USTEM1,n=12; USTEM2, n=17) vis-à-vis five PSO indicators: 1) academic self-efficacy in STEM(ASESTEM; an average of 3 items), 2) self-efficacy in performing STEM tasks (STEMTaskSE;an average of 4 items), 3) sense of belonging in STEM (STEMSB; an average of 18 items), 4)STEM self-identity (STEMSI; an average of 4 items), and 5) sentiments about staying in a STEMmajor
associated with a variety of student outcomes. Additionally, modified versionsof previously validated instruments were used to measure teachers’ motivation for participatingin the K12 InVenture Prize program [15] and teachers’ self-efficacy for teaching engineering andentrepreneurship [16]. Participants A total of six teachers from our focal region began the survey. Of these, two discontinuedthe survey during the demographics and teaching background sections; a total of fourrespondents completed the survey. All four teachers who completed the survey are women, andall four teachers are White. For all four teachers, the 2018-2019 school year was their first yearimplementing the K12 InVenture Prize program. Two teachers implemented in a
/perceived confidenceand interest/values in STEM has progressed over the past two decades, studies of students’motivational orientations (intrinsic versus extrinsic) in STEM are quite limited.Perceived confidence and self-efficacy strongly influence academic motivations [44] and serveas mediators of learning engagement and persistence [8]. As such, STEM educators areconcerned with how learners cultivate a strong sense of efficacy and expectations of success.Indeed, measurement of self-efficacy and perceived competence represents an area of notableprogress in STEM education research. Gendered patterns in learners’ perceived competence andself-efficacy within gender-role stereotyped domains such as mathematics and engineering arewidely reported [45
preparedness10. Workshop(s) on product commerciali- 1 2 - 2 3 4 2zation Table1: Ratings of the overall summer bridge experienceStudent self-efficacy was assessed using the Engineering Skills Self-Efficacy Scale [6]. The scalewas developed to assess the different dimensions of self-efficacy for undergraduate studentsacross various engineering-related disciplines. The measure reports three sub-scales:Experimental Skills, Tinkering Skills, and Design Skills. To assess the effectiveness of theadditive manufacturing project-based experiences, the project evaluator wrote four itemsmodeled on the existing items on the Engineering Skills Self-Efficacy Sub-Scales
onassessing students’ self-confidence across key biomedical engineering competencies. As therewas no existing questionnaire for this particular subject, we developed this questionnaire byfollowing the same question structure as the SE-12 Questionnaire for measuring medical studentself-efficacy for clinical tasks [14]. Students were asked to rate their level of agreement withstatements that gauged their confidence in applying technical knowledge in the field, includinglaboratory basics, biomedical device challenges, antimicrobial practices, cytocompatibility, andmechanics. The self-efficacy questionnaire was administered at the beginning and end of thesemester. Each instance of the questionnaire took 20-30 minutes to complete. In Spring 2025,the same
they lackthe training and self-efficacy to effectively implement open-ended engineering problem-solvingexperiences in their classrooms. This is additionally difficult for schools in rural and NativeAmerican settings, as resources and support may be limited [3]. Curriculum is often presentedfrom a Western framework that does not incorporate cultural knowledge, values, and beliefsembedded in a community [4]. Oftentimes, engineering design tasks are thought of as aculturaland devoid of community inclusion and values. However, engineering design is inherently acultural endeavor as problems needing engineering solutions or design thinking are situated in aspecific community and need community solutions. Furthermore, the engineering design
environment as an intern/co-op”(Atwood et.al, 2021). However, only 41.5% of historically marginalized populations completedan internship (Atwood et.al, 2021) by graduation. Similarly, only 47.6% of first-generationstudents completed an internship (Atwood et.al, 2021). Lack of internship or co-op can lead tounderemployment and significantly less lifetime earnings. Lack of internship also could beattributed to the student’s lack of social capital. According to NACE, first-generation studentsreceive lower salary offers compared to their continuing-generation counterparts (Eismann,2016). Additionally, self-efficacy is crucial for the individual’s ability to complete a task(Huang, 2003).MethodsHaving explicit instruction around communication skills
not absolute characteristics,and the Felder-Silverman model accounts for “balanced,” “moderate,” and “strong” preferenceswithin each dimension. However, because learning styles describe the cognitive processesinvolved in problem solving, it may be argued that individuals with more balanced learningstyles will be better problem solvers. Originally, our study focused on the correlation betweenstudent learning styles, problem solving strategies, self-efficacy, attitudes/perceptions, andperformance in an introductory undergraduate chemical engineering course at a largeMidwestern university, in an effort to better understand our student population and provide abasis for curricular development. We were interested in understanding whether there
specified). In addition, we assessed social cognitive variables related to educationaland career decision making, including engineering self-efficacy, expectations for the field ofengineering, commitment to major and degree completion. In 2019, students were asked if theyidentified as a member of the LGBTQ+ community, allowing for a better understanding of thesestudents’ experiences. Data from all three survey years were combined to investigate trends oncritical measures related to persistence in engineering. We found that students’ assessment of theeducational environment (professors and student interactions) were relatively stable, while otheraspects of the environment (experiences of stereotyping and harassment) significantly increasedacross the
students were male. Students’ ranged in age range 14 to 18.MeasuresA single pre-post measures was administered before the start and end of the 3-week class project.The Academic Self-Description Questionnaire II (ASDQ-II) 39 includes a sub-scales based onparticular subjects of interest and self-efficacy towards them including computer studies,mathematics, industrial arts, science, and general day-to-day self-efficacy. Each sub-scalecomposes of 8 items that assess identification with and perceived efficacy in academics, forexample for the case of ”Computer Studies”, items would include assessment statements such as“Compared to others my age I am good at COMPUTER STUDIES classes”). The ASDQ-IIfollows a 8-point Likert scale where participants are
by stating “self-efficacy is not perceived skill; it is what I believe I can do with my skills under certainconditions…my ability to coordinate and orchestrate skills and abilities in changing andchallenging situations” (p. 278). Bandura and others have written extensively about the differences between self-efficacyand self-esteem. In addition to differentiating the constructs conceptually, there is some debateregarding how self-efficacy and self-esteem are interrelated. Bandura67has argued self-efficacyis independent and unrelated to global measures of self-esteem. This view was captured byBandura in his statement- “the fact that I acknowledge complete inefficacy in ballroom dancingdoes not drive me to recurrent bouts of self
other courses includingvideo content and be less resistant to this form of instruction.To get insight into the effects of the courses focus on learning and applying design theory, aninstrument was used to measure participant engineering design self-efficacy. The instrumentwas designed and validated by Carberry et al [20]. The tool measures individual’s self-efficacytowards engineering design tasks. Self-efficacy is an individual’s belief in their ability tocomplete a specific task [21]. This instrument examines four aspects of an individual’s self-efficacy: 1) Confidence, 2) Motivation, 3) Expectation of Success and 4) Anxiety towardscompleting engineering design [20]. The instrument was administered at the beginning and endof the Hybrid2
uniqueresearch experiences must be identified for 100 students in laboratories across campus.Furthermore, the arrangement of internships depends upon strengthening and expanding thenetwork of regional industries, companies, and health services organizations. This requiresconsiderable work, however, our extensive faculty network and alumni have been supportive inproviding resources and opportunities for current WISE students.Preliminary FindingsTo measure the effectiveness of the new WISE curriculum in meeting its goals, incomingfreshmen (N = 58) were surveyed at the end of the fall semester in 2017. Baseline data werecollected to explore the following research question: How does participation in the WISEcurriculum impact students’ self-efficacy, career
engineering design is unclear. The objective of thisresearch is to measure whether students who have service learning experience have a deeperunderstanding of sustainable engineering than their counterparts who do not have servicelearning experience. The research design is comprised of three evaluations: sustainableengineering design, self-efficacy towards sustainable engineering, and epistemological beliefstowards general engineering. Each evaluation will be performed on engineering students at threedifferent institutions which employ varying types of service learning programs; Tufts University,Michigan Technological University, and University of Colorado-Boulder. Students enrolled inthe Civil and Environmental Engineering Senior Design/Capstone
an existing survey instrument that measured: (1) the extent students’ value sustainableengineering (including beliefs of importance, interest, and utility value to achieve future careergoals; 6 items, 7-point scale); (2) affect and behavior related to sustainable engineering (4 items,7-point scale); and (3) students’ self-efficacy or confidence in their ability to understand andincorporate societal, economic, and environmental sustainability issues (6 items; 0 to 100 scale).The value items map most closely to the CEBOK3 rubric for the affective domain of thesustainability outcome, while self-efficacy relates to personal perceptions of cognitive domainoutcomes. Sustainable engineering (SE) value was high among both CE seniors and
test scores, and thegrades and number of semesters in math, science and English courses in high school. The non-cognitive variables were collected through Student Attitudinal Success Instrument (SASI). Thefirst phase of SASI covered the following nine constructs: Leadership, Deep Learning, SurfaceLearning, Teamwork, Academic Self-efficacy, Motivation, Meta-cognition, Expectancy-value,and Major Decision. Later in 2007, five new constructs were added into SASI. These newconstructs are: Goal Orientation, Implicit Beliefs, Intent to Persist, Social Climate and SelfWorth.Cognitive and non-cognitive data, as well as students’ retention status after first year have beencollected from the freshman cohorts of 2004-2009, with 1500 to 1700 entering
format of our summer camp, which we project would helpeven more our main goal, is to organize follow-up summer camps (in the following year)with the same participants. Exposing girls repeatedly to engineering concepts will providethe necessary reinforcement of the main topics and will foster the desire to pursueengineering careers. In addition, it is also desirable to maintain a database of participantsand their contact info (with parental consent) to keep track of their careers later in theirlives. Such data would present concrete statistics about how many participants willeventually pursue careers in engineering.To measure the improvement in perceived self-efficacy, we plan to update the exitquestionnaire with an additional question, “I
). After the completion of the summer program, teachers completed a post-survey (n =7-8 ) ontheir self-efficacy for teaching engineering during the Fall to measure any perceived changes inbeliefs as a result of the summer program. The results of the pre-post survey are found in Table3.Table 3: Teachers reported self-efficacies in teaching engineering pre-post summerprogram. Strongly Moderately Slightly Slightly Moderately Strongly Disagree Disagree Disagree Agree Agree Agree 1. I can discuss PRE how given 20% 10% 20% 0% 40% 10% N=10
psychosocial construct values forFeelings of Inclusion, Coping Self-Efficacy, and Belonging Relative to Community are nearlyidentical (standard deviation of .04 or less) from spring of 2020 through spring of 2022. The labfocused skill efficacy for Design and Experimental skills, also maintained steady average valueswith a standard deviation of .04 or less. These values imply, that for the students who completedthe survey, the sudden switch to a virtual format was successful in supporting these constructs.Table 2. Constructs measured in surveys to date Construct Average value of mean per semester (S.D
evaluation instruments were built from psychometrically sound instrumentsand scales that include the Career Interest Questionnaire and Modified STEM Semantics Survey(Tyler-Wood et al., 2010), Entrepreneurial Self-Efficacy and Intention (Wilson et al., 2007),Student Attitudes toward STEM Survey (Mahoney, 2010); STEM Semantics Survey (Tyler-Wood et al., 2010), Sources of Self-Efficacy Scale (Britner & Pajares, 2006), and a 21st CenturySkills Assessment/Rubric. Specifically, the process evaluation was designed to measure both quality and intensity ofSTEM-Inc activities in order to monitor the short-term and formative results of activities andservices, validate program components, and determine whether activities were of sufficientquality and
no effect on faculty members’ self-efficacy related toculturally responsive classroom management (CRCMSE) and engineering pedagogy (TESS).Faculty reported moderately high self-confidence on all CRCMSE measures (range: 2.06-2.50 on0-3 pt Likert), and there were no statistically significant gains in these measures from pre- topost-workshop. Similarly, faculty also had moderately high self-confidence on TESS measures(range: 3.33-4.72 on 0-5 pt Likert); and pre- vs. post-workshop gains were reported for two of 15survey items. Specifically, faculty reported gains in confidence related to their ability to guidestudents in the engineering design process or scientific method (d=1.15, p=0.009, n=18) and self-confidence in encouraging critical
measured the students’ degree of self-efficacy to remember and understand course content as well as to solve, analyze, evaluate, andcreate a problem related to soil structure, seepage, effective stress, consolidation, and shearstrength. Students were asked to rate on a five-point Likert scale where ‘1’ stands for “cannot doat all” and ‘5’ stands for “certainly can do”. Second, the ‘Student Self-Efficacy for theApplication of Knowledge’ survey included 21 questions developed by the researchers tomeasure the student’s self-efficacy to accomplish tasks associated with the content in the course.Students were asked to rate the same five-point Likert scale. Lastly, the ‘Self-RegulatedLearning Strategies’ survey included 13 questions that were developed
uses a combination of multiple choice and Likert-type summatedrating scales to address four measures of students’ energy literacy - energy-related knowledge(38 items), attitudes toward energy issues (13 items), feelings of self-efficacy (4 items, containedwithin the attitude subscale), and energy consumption behaviors and intentions (10 items).Questions contained in the Energy Literacy Survey are broad in nature, and are not intentionallyrelated to the course content. Table 3: Summary of Data Collection Procedures Administered to… A Measure of… Quantitative
attended the Bridge remotely, still found the experiencetransformational. In a case study interview conducted by Ruxton Consulting, one student attributedtheir success to the Bridge saying, “I really think I wouldn't be here. I wouldn't be studyingengineering without the creation of the Bridge program.” (Ruxton Consulting Evaluation Reportpresented to the PI, 2022).Students also reflected on how their effort, within the structure of the Bridge, contributed to theirimproved self-efficacy in math. As one student shared, “It's not a test of your finances, or yourbrains. It's a test of how hard you can work, and I think that's a great factor to measure someoneby.” Another student acknowledged how much work was ultimately needed in order to be readyfor
students’ perceptions of industrialinternships. However, students’ self perceptions of their skills and abilities, a concept called“self-efficacy,” are a critical aspect of their ability to perform in a given situation [7]. Anunpublished work by researchers at the Cambridge-MIT Institute studied how cooperativeeducational programs affected the self-efficacy of engineering students[8] and found thatcooperative educational programs exerted a positive influence on students’ self-efficacy.Academic and Labor Market Outcomes of Cooperative EducationStudies have been done to investigate the positive academic and labor market outcomes resultingfrom cooperative educational experiences in engineering disciplines. As examples, both Gardneret. al.[9] and
isevident and supported by Table 2. Despite this lack of coherence, these studies have beenimportant first steps in exploring specific aspects of identity development in engineering. Closely related to identity but not explicitly stated, others have provided a review andanalysis of existing research on the measurement of the characteristics of engineering students inorder to illuminate factors that affect college enrollment and retention.12 The authors, Li,Swaminathan, and Tang, found that many researchers are specifically looking at the factors thathelp or hinder the matriculation of underrepresented groups into engineering. Marra, Rodgers,Shen, and Bogue conducted a multi-institution study on self-efficacy and women engineeringstudents.36