population of the engineering students and retaining them to the end of their educationaljourney, and toward the ultimate goal of professional licensure.Service leaning has been proven to be an invaluable tool to recruit and retain engineering students, a studyconducted by Astin et al (2000) found that in a study of 22,000 students, integrating service learning hadsignificant positive effects on 11 outcome measurements including critical thinking skills, values,leadership and self-efficacy. Eyles & Giles (1999) studied 20 universities and the effect of a service-learning based curriculum on over 1500 students. The results indicated an increased positive impact in the
: http://www.ncca.ie/uploadedfiles/JuniorCycleReview/ESRIComment.pdf23. Bandura, A. (1997). Self-Efficacy: The exercise of control. New York: W.H Freeman24. Puccio, G. J., Wheeler, R. A., & Cassandro, V. J. (2004). Reactions to creative problem solving training: Does cognitive style make a difference. The Journal of Creative Behavior, 38, 192-216.25. de Bono, E. (1970). Lateral thinking. London: Penguin Group26. State Examinations Commission. (2009). Chief examiners report on materials technology Wood. Athlone: State Examinations Commission.27. Houtz, J. C., & Krug, D. (1995). Assessment of creativity: Resolving a mid-life crisis. Educational Psychology Review, 7(3), 269-30028. McAuley, E., Duncan, T., &
, pp. 115–127, 2009.[15] D. E. Hammond and C. Shoemaker, “Are there differences in academic and social integration of College of Agriculture Master’s students in campus based, online and mixed programs?,” NACTA J., vol. 58, no. 3, pp. 180–188, 2014.[16] B. Simunich, D. B. Robins, and V. Kelly, “The impact of findability on student motivation, self-efficacy, and perceptions of online course quality,” Am. J. Distance Educ., vol. 29, no. 3, pp. 174–185, 2015.[17] “Research-Based Web Design & Usability Guidelines,” Washington, DC.[18] S. J. Guastello, Human Factors Engineering and Ergonomics: A Systems Approach, 2nd ed. Boca Raton, FL: CRC Press, 2014.[19] N. Sclater, Learning analytics explained. New York, NY
research provides insight into this issue through partnerships between PSTs andUESs and faculty. In the Paired Peer Mentors project (Fogg-Rogers et al., 2017), pairs of PSTsand engineering students presented engineering design challenges to primary school children.Both groups of college students showed sizable gains in teaching engineering self-efficacy andsubject knowledge confidence after the project. In a study exploring a similar partnership model,PSTs and engineering students collaboratively planned robotics activities for early childhoodstudents using LEGO WeDo robots (Bers & Portsmore, 2005). PSTs used robotics to helpelementary students explore concepts in math and science supported by engineering studentpeers. Although these studies
-genderprograms like FEMME can be particularly effect in reaching young girls and changing theirattitudes. Initial evaluations of the FEMME program have been positive but they have beenprimarily formative in nature. The Middle School Students’ Attitude to Engineering, Scienceand Mathematics Survey has been developed to measure middle school students’ overallattitudes to engineering, mathematics and science; their knowledge about engineering careers;their self-efficacy in relation to engineering and technology-related skills and who is talking tothem about careers in engineering. All students who attended one of the 2006 summer programsat the Center for Pre-College Programs were asked to complete the survey at the beginning andagain at the end of their
’ levels ofconfidence were mixed. Female and male students differed by less than one percentage point;Asian students had the highest expectations (94.1% responded “OK/Pretty Well or Very Well”),with Hispanic/Latino students slightly lower (91.6%), and Black/African American studentsslightly lower still (90.8%). By school-level, students varied slightly: elementary students hadthe most confidence (92.9% responded “OK/Pretty Well or Very Well”) and high school studentshad the least confidence (88.1%). Overall, though, these demographic differences were relativelysmall with regards to self-efficacy in these core STEM areas.Table 2. Upper Elementary and Middle and High School Student Demographic Characteristics
to rely upon the efforts of the stronger membersof their teams. Of course, this decision making process was reflected in both their knowledge ofthe subjects and the results on their examinations. Their research papers, also, were animportant effort to aid the students in enhancing their self-efficacy through completing researchand producing a professional paper that could be presented at a regional or national conference.Though there was much anticipation at the beginning of the class, many of the students wereinterrupted in their efforts due the fact that a number of the students were completing their seniordesign projects. Instead of using their time management skills in this situation, where they hadmultiple assignments and tasks to
mathematics aptitude measured using ACT and/or SAT Math scoresand not only enrolling in, but also performing well in advanced science (i.e. physics) andmathematics (i.e. calculus) courses in high school.1-3 Additionally self-efficacy, determinedfrom student survey responses to questions designed to gauge their confidence in theirquantitative abilities, parental educational attainment and geographic location (i.e. urban versusrural home) have been found to impact engineering student persistence and achievement. 4,5 Oneof the primary first year indicators is grade point average (GPA), which is indicative of students’quantitative and analytical capabilities, as first year engineering curricula are dominated bymathematics, science and fundamental
model to prepare students for interdisciplinary collaborationbetween engineers and other professionals.References[1] Raju, P.K., and Sankar, C. “Introduction To Engineering Through Real World Case Studies”. In ASEE Annual Conference & Exposition, Chicago, Illinois. Conference Proceedings, 2006. https://strategy.asee.org/671, retrieved on February 5, 2024.[2] Daniels, J., Sanlillan, S.T., and Saterbak, A., “Tracking skills development and self- efficacy in a new first-year engineering design course.” In ASEE Annual Conference and Exposition, Conference Proceedings, 2018. 8[3] Rippon, S., Collofello, J., and Hammond
Area and Salinas and shown to improve participants’ interest in science,content knowledge and self-efficacy. The Family Science Courses are designed and taught byengineering undergraduate and graduate students to families at schools in the evenings. EachFamily Science Course consists of five evening sessions of two hours each. Families are invited(including younger siblings). Formative assessments such as Exit Slips (three questions checkingfor content understanding) are conducted at the end of every session. Pre and post tests areconducted in each Family Science Course. Food is provided at every session. Instruction istranslated into Spanish if the majority of families are Hispanic and non-English speaking. Topicsillustrate the real-world
Learning Questionnaire (MSLQ) is a self-report instrumentdesigned to assess college students’ motivational orientation and their use of different learningstrategies for a college course. According to [14], the instrument is a measure of student self-efficacy, intrinsic value, test anxiety, self-regulation, and use of learning strategies. Constructsfrom this survey center on measures of the types of learning strategies and academic motivationused by college students. This instrument uses 44-items with a 7-point likert-type scale withstatements focused on student motivation, cognitive strategy use, metacognitive strategy use, andmanagement of effort. Additionally, a number of researchers have also utilized the MSLQ toexamine whether there is a
., Usher, E. L., Li, C. R., Economy, D. R. and Kennedy, M. S. (2016), Measuring UndergraduateStudents' Engineering Self-Efficacy: A Validation Study. J. Eng. Educ., 105: 366–395.8 Burton, J. D. and White, D. M. (1999), Selecting a Model for Freshman Engineering Design. Journal ofEngineering Education, 88: 327–332.9 Gunn, C., & Somerton, C., An Engineering Laboratory Experience For A Freshman Engineering Class Paperpresented at 2004 ASEE Annual Conference and Exposition, June 2014 Salt Lake City, Utah.10 Alava, J.D. and Gardiner, K.M. The Development of the First Year Engineering Experience. Proceedings of Fall2010 Mid-Atlantic ASEE Conference, October 15-16, 2010, Villanova University. (http://www.asee.org/documents/sections/middle
measures were used in several large-scale quantitative studies, andincluded three constructs: performance/competence belief (related to self-efficacy); interest inthe subject; and feelings of recognition (i.e., feeling that others see them as the type of personthat can do the work) [42]. Together, these three constructs are reliable in describing students’self-beliefs, which comprise a students’ identity, and “are predictively valuable forunderstanding career choices” [42]. The theoretical framework for the instrument stemmed fromsocial identity theory and symbolic interactionism, and Godwin focused on the internal dynamicsand roles that impact behavior. Godwin concluded that the results provide strong validityevidence for the developed instrument
on and explicate their mental models and to adaptexternal knowledge. Bittner and Leimeister (2014) described that if team members are engagedin some activities of self-reflection on and visualizing their understanding before a specific teamtask, the team can develop TMMs more efficiently. In a similar sense, Bierhals et al. (2007)mentioned that each member’s perceived self-efficacy in a specialized domain related to theteam task can positively affect the development of TMMs. Also, Nemanich, Keller, Vera, andChin (2010) determined that team members’ ability to evaluate and assimilate externalknowledge is positively related to the team’s ability to develop TMMs. Furthermore, Kleinsmaanand Valkenburg (2008) described team members’ ability to
development, and student learning in integrated STEM environments. Dr. Alemdar is currently PI and co-PI on various NSF funded projects. Her expertise includes program evaluation, social network analysis and quantitative methods such as Hierarchical Linear Modeling, and Structure Equation Model- ing. She received her Ph.D. in Educational Policy, with a concentration in Research, Measurement, and Statistics, from Georgia State University.Dr. Michael Helms, Georgia Institute of Technology Dr. Michael Helms is a Research Scientist at the Georgia Institute of Technology. He received his Ph.D. in Computer Science from the Georgia Institute of Technology, where his research focused on improving design creativity.Dyanne Baptiste
assessing not only what they learnedbut how they learned [2], [3]. Specifically, SDL allows students to create their learning goals,diagnose resources required to meet those goals, and finally self-assess against the goals theycreated [4]. Seminal studies on SDL suggest the importance of the instructor to design learningenvironments in which students can choose their path in a safe and supported space [5], [6].Further, the intentional design of these environments is essential for students to develop theirSDL skills and self-efficacy in the college classroom [7], [8]. The SDL research reveals whenstudents apply SDL techniques they can apply their learning strategies to gain a deeperconceptual comprehension of the problems they are trying to solve
inengineering, or women in STEM (Science, Technology, Engineering, Mathematics) [2] ,[3], [4],[5]. Even if the model is not explicit, components of engineering identity such ascompetency/self-efficacy and recognition (from herself and others) are still discussed [6], [7].Godwin’s Engineering Identity Model [2] for early post-secondary students (as thisautoethnography fits into this category) is situated in the idea of “role identity” in that “theindividual attaches to the context of a social and cultural role. An individual has as many selvesor identities as he or she has groups of people with which he or she interacts. Some identitiesbecome more salient based on the particular context and social situation in which an individual isimmersed” [2]. The
students interests towards pursuing a graduate degree.The physical and psychological impacts of student involvement, such as attending social events,giving oral presentations, being part of a group, club, organization, etc., have been studied widelyby scholars [31][32][33][34]. They have shown a major role in students’ self-efficacy andpersistence and positively impact students’ academic autonomy, career, and lifestyle planning[32][35][36][37]. “Academic involvement, involvement with faculty, and peer involvement” arethe three most powerful involvement forms according to the literature [31]. Likewise, learning ina group is an effective practice in promoting greater academic achievement, promising attitudestoward learning, and increasing
Puentedura’s SAMR (Substitution - Augmentation -Modification - Redefinition) framework [1], examining the results of primary research withinstructors and students experiencing these tools and kits, in a Winter 2021 course in theStanford University department of Aeronautical and Astronautical Engineering. The instructorswho developed the course were interviewed using a structured set of questions, and the resultsanalysed through qualitative coding of the transcribed interview content to find common themes.Students studying the course were invited to participate in a pre-and post- course surveydesigned to evaluate and describe their self-efficacy and experiences with the course’s tools andkits. We note that the supplied kits were just one piece of
students’ digital literacies and assessment. Recently, Dr. Hsu has received a seed grant at UML to investigate how undergradu- ate engineering students’ digital inequalities and self-directed learning characteristics (e.g., self-efficacy) affect their learning outcomes in a virtual laboratory environment during the COVID-19 pandemic. Dr. Hsu’s research interests include advanced quantitative design and analysis and their applications in STEM education, large-scale assessment data (e.g., PISA), and engineering students’ perception of faculty en- couragement and mentoring.Dr. Yanfen Li, University of Massachusetts Lowell Yanfen Li is an Assistant Teaching Professor at the University of Massachusetts Lowell. She received
conducted a study comparing the performance of students who did and did not useavailable forms of SI and correlated performance outcomes with factors deterring students fromusing the offered forms of SI. Our focus this year is to identify statistically significant trends inour data from this year’s and last year’s classes and assess the impact of level of participation inSI on student self-efficacy and attitude towards SI for freshmen enrolled in a required generalchemistry course.To understand a student’s choice to participate in SI and to determine correlations with courseassessments and grades, students enrolled in a required general chemistry course were surveyedat the beginning and at the end of the semester. This year (fall 2014) 524 students
strategies can help boost self-efficacy, which is particularlyimportant for upper-level classes 9 . The work-in-progress presented here represents an effort toidentify effective learning strategies and to allow current undergraduates the opportunity learnfrom their peers; however, this work does not directly discuss how to achieve successful tutoring,focusing instead on examining if students know the services and strategies and use themappropriately. This differs from the more common exploration regarding the intention of studentsand college professionals regarding help-seeking. In addition, few studies have included theInternet among the sources of help sought 10 . This study contributes to the literature byspecifically including the Internet as a
circuits.This can imply that instructors focused on improving students’ learning in classes by introducingnew pedagogies or interventions with more direct effects, rather than by increasing students’motivation such as their self-efficacy in learning circuits or sense of belonging in engineering. Inother words, it is concluded that most of the focus was on “how to learn circuits better” not on“why you need to learn circuits.”From 2014 to 2016, metacognitive and cognitive interventions were not as popular, with mostinterventions being related to flipped classrooms and management strategies. During 2017 and2018, interventions were mostly related to metacognition and flipped classrooms. However, afterthis period, from 2019 to 2020, the focus shifted to
, they are more likely to overcome obstacles in their academic journey, allowingthemtobuildresilience.Academicresilienceissignificantlyassociatedwithenhanced performance and a greater likelihood of achieving educational goals, as resilient students are better able to overcome challenges and maintain motivation [17]. Research supports that self-efficacy,orbeliefinone'sabilities,enhancesmotivationandengagement,whicharecrucialf oracademicsuccess[18].Higherself-efficacyisassociatedwiththeuseofdeepercognitiveand metacognitive strategies, ultimately resulting in better academic
Negative Affectivity and Their Relation to Anxiety and Depressive Disorders," Journal of abnormal psychology (1965), vol. 97, no. 3, pp. 346-353, 1988, doi: 10.1037/0021-843X.97.3.346.[13] R. W. Hass, J. Katz-Buonincontro, and R. Reiter-Palmon, "Disentangling Creative Mindsets From Creative Self-Efficacy and Creative Identity: Do People Hold Fixed and Growth Theories of Creativity?," Psychology of aesthetics, creativity, and the arts, vol. 10, no. 4, pp. 436-446, 2016.[14] H. F. Posada-Quintero, J. P. Florian, A. D. Orjuela-cañón, T. Aljama-corrales, S. Charleston-villalobos, and K. H. Chon, "Power Spectral Density Analysis of Electrodermal Activity for Sympathetic Function Assessment," (in English
preparation programs at our institution. We believe thelevel of mathematical content is high compared to similar programs elsewhere. We are of theopinion that the multidisciplinary nature of our programs (all four elements of STEM) arebeneficial. Preliminary course surveys and measurements of math anxiety and teaching self-efficacy indicate that the integrated STEM teacher candidates do experience substantialimprovements over the course of their curriculum.IntroductionOur institution supports two Science, Technology, Engineering and Mathematics (STEM)teacher preparation programs. One program, referred to as the Math/Science/Technology(MST) program, is an elementary [preK-5] program and was started in 1998. The secondprogram is a secondary 6-12
highschool internships that engage students in authentic STEM environments [2], [3]. High schoolinternships are especially impactful for underrepresented minority (URM) female students inSTEM [1]. Prior research has shown that these internship opportunities can increase students’sense of self-efficacy in STEM fields, give students insight into career paths they might nototherwise be exposed to, and increase students’ interest in and pursuit of STEM-related majorsand careers.The home environment can also provide opportunity for students to increase and strengthenSTEM identity and the consideration of STEM careers. A model for STEM identity has beendeveloped as a framework building on disciplinary studies and includes the interplay of threeelements
-school outreachprogram in engineering design for middle school students (ages 11-14), and how instructorsviewed the successes, challenges, and tensions of their students’ laboratory experiences. A challenge associated with NGSS and ASEE implementation is the meaningful integrationof science and engineering knowledge and skills in precollege teaching and learning. Researchhas identified issues that science teachers encounter with integrated STEM instruction, includinglack of relevant content knowledge, lack of administrative support, and weak self-efficacy inengineering pedagogy [4,10,11]. Research in STEM integration education has suggested thatinnovative instructional models and curricular resources are needed to demonstrate how scienceand
still in its infancy, studying the HC in engineering is gaining momentum across nationaland international circles [2]-[16]. Traditionally viewed as implicit messaging for women inengineering learning and research environments [2], [3], Villanueva [4] (re)introduced the HC asa structural framework that contains several interconnected pathways (awareness, emotions, self-efficacy, and self-advocacy; each are described in the paragraph below). According to sociologyscholars [17]-[19], structural frameworks consider how moving parts of a system (e.g., commonnorms, customs, traditions, and cultures) are structurally supported and sustained to promotestability and solidarity amongst its actors (individuals or groups). In HC, the interconnected