area involvesuniversities with small proportions of URMs. Thus, continued study of the impact of thesefactors on more diverse student populations is also necessary to better capture the calculusexperience of URM engineering majors. The purpose of the study was to examine student andclassroom-level factors that influence course performance measured by course grade. This studyfocused on two engineering-related psychosocial factors: (1) engineering self-efficacy and (2)engineering sense of belonging, and three mathematics-specific psychological factors which werefer to as math motivators, (1) math interest, (2) self-concept, and (3) anxiety. Classroom levelfactors included active engagement practices, proportion of females, proportion of
Table 2, Model 3). However, sense ofbelonging item B3, a reverse-worded survey item, showed moderate cross-loadings with most“self-efficacy” items, suggesting that the reverse-wording may have been confusing or that thisitem does not exclusively measure the “belonging” construct but may overlap conceptually withaspects of “self-efficacy”. As such, we determined that removing this problematic item wouldlikely improve the model’s fit.Stage 4 Results (Model 4)Excluding B3 resolved its cross-loading issues, yielding the best-fitting model (see Table 2,Model 4, which is the final iteration of the measurement model). No additional largemodification indices emerged, suggesting no further modifications were warranted. This modelserved as our final
and measure their course preparedness. Welch's t-test was also used to determineif there was any difference in the students' performance on the common final exam.For the test anxiety Likert questions, a score ranging from 5 to 20 was obtained by summing thescores for all five questions, with 1=almost never and 4=almost always. Paired t-tests wereperformed for both grading methods to identify any changes over the semester after taking thecourse. In the case of the self-efficacy questions, scores for each category (e.g. masteryexperience, vicarious experience, social persuasion, and physiological state) were averaged afterbeing set on a scale of 1=definitely false to 6=definitely true. Paired t-tests were performed forboth grading methods to
investigated. Demographic information for thetotal analytic sample is as follows: 76% self-identified as men, 95% White, 50% were onEngineering Track 1, 30% were on Engineering Track 2, and 20% were on Engineering Track 3.Measures Engineering Self-Efficacy. Students’ confidence in their ability to complete necessarysteps for obtaining their engineering degree was measured using a three-item instrumentdeveloped by Lent and colleagues [45]. The items were rated on a 5-point Likert scale (1-noconfidence to 5-complete confidence) where participants indicated their level of confidence intheir ability to complete each step necessary to obtain their engineering degree. Engineeringself-efficacy scale scores were derived as the average of all items
Non-URM ContGen First Gen All (n=45) Male (n=25) URM (n=15) (n=20) (n=30) (n=24) (n=21) Pre 3.9148 4.16 3.6084 3.8889 3.9667 4.0174 3.7977 Post 3.9889 4.13 3.8125 4.0583 3.85 4.0104 3.9643Self-efficacy: There were no significant changes in students’ perceived self-efficacy in bothmastery experiences and verbal persuasion measures over the semester, although a slight declinewas noted across most demographic subgroups. There were no significant differences betweenstudents’ self-efficacy (mastery) by gender, URM, or first-generational status at
in anxiety levels from aninitial mean of 11.97 to 9.78 by the end of the semester (p < 0.001). Additionally, masterystudents showed significant improvements in self-efficacy in mastery, vicarious experience, andsocial persuasion (p = 0.005, 0.012, 0.018), which was not observed in the traditional group. Wecompared students' placement scores between two groups and found no significant difference inpreparedness (p-value=0.49). Despite the expectation that constant revisiting of topics in masterygraded sections would enhance retention and performance, there was no significant difference inperformance at the end of the semester (p-value=0.86). However, the final grade distributionsbetween the two groups indicated a considerable difference
.”Research QuestionsOur main research questions are as follows:● Does students’ self-efficacy in mathematics and engineering increase when mathematical and engineering concepts are introduced and surveyed in a hands-on fashion before students take more theoretical courses?● Are we better able to retain FGLI students in engineering if they are introduced to mathematical concepts through engineering applications during the summer before their first term?Program DescriptionFirst-generation, low-income (FGLI) students admitted to xxx were invited to participate in a 3-week long summer program aimed at helping them build a cohort, develop a support network,sample academic classes, determine where to go for help, and explore different possible
demandstrategies such as setting up milestones and actively coaching the students [21]. More facedchallenges are institutional constraints such as limited budgets and new ideas requiring extensiveplanning. Lastly, most PSI research focuses on psychology and behavior analysis of students,raising concerns about the generalizability of findings to other disciplines and diverse studentpopulations [21]. Accordingly, careful planning was done in Math Launch to benefit from PSIand address identified challenges. The customized PSI tenets in Math Launch pedagogy are:1. Preparation of written materials: ALEKS was set up so it provided an explanation page before a student attempted an exercise which enhanced student understanding and helped with improving self