disengage in certain circumstances. Although it identifies eight dimensions of moral disengagement (moral justification, euphemistic labeling, advantageous comparison, displacement of responsibility, diffusion of responsibility, distortion of consequences, attribution of blame, and dehumanization), the scale is most correctly used as a measure of the single higher order concept of moral disengagement. • Experiences (17 items): Students were asked about their participation within the last two years and their plans to participate in the future in seventeen types of experiences: 1. Volunteer regularly (1+ time per month for 6 months longer) 2. Mission or volunteering trip (any location) 3. Work or internship in a non-profit
, and responding to students’ ideas in ways that help students build on their priorknowledge (Richards & Robertson, 2016; Sherin, Jacobs, & Philipp, 2011). As Ball & Cohen(2013, p. 16) put it, “Examining student thinking is a core activity of [teachers’] practice.” Inorder to help teachers develop their responsiveness, teacher educators and teacher professionallearning communities typically rely on artifacts of classroom practice (i.e. examples of studentwork, video or audio recordings of classroom events, or field notes on classroom events) toanalyze pedagogical moves/approaches, to investigate the possible consequences of theirpedagogical approach for students’ learning, and to consider intentions and plans for futurepedagogical
cooperative learning6 techniques to facilitate activelearning on the subject matter for an hour. The LTMs ranged in size from 10 students to up to 20students. The students would meet on campus in a classroom with a peer mentor one hour aweek. Additional optional study sessions were also offered throughout the week. In addition,social activities were planned to help the students to get to know each other. To make sure thatthe one hour a week meeting appeared on the students’ schedules, a zero credit course wascreated. Students signed up for the LTM session during summer orientation with their advisor’sassistance. Once registered, the LTM course would then reserve the classroom space and showup on the students’ class schedule which reminded students to
with them in December and we saw that they did not have anything manufactured on the bike yet and the competition was in April. It was just bad planning, just “let's get this over with type thing.”One competition organization representative, as well as the advisors of some of the moresuccessful teams, told us that most students and many faculty view these competitions asengineering design-build competitions, yet they are actually engineering managementcompetitions. One advisor offered the analogy of the difference between making a movie on thestudio set, where all resources are at hand and making a movie on location, where all resourcesmust be taken to the remote locale. Successful productions have anticipated all eventualities
typical lessons, when designing for failure,one would plan to engage in sustained inquiry after failure is encountered (Tawfik et al., 2015).Failure in engineering educationWhen practicing engineers engage in designing small physical products (the kind of designingmost similar to many tasks given to elementary students), they create and test models of theirdesigns. Initial “models” may include mathematical models, then later digital models, andfinally, sometimes, physical models (possibly prototypes, at full scale or model scale). Practicingengineers create and test these constructions, then use the previous test results as feedback toiterate and improve their design. In this way, interpreting failure (in the broad sense of notacceptably meeting
social system; and (2) “the constructed type,” which represents the “second order construct” and is created by researchers [44]. • The constructed type is “a construct made up of abstracted elements and formed into a unified conceptual pattern wherein there may be an intensification of one or more aspects of concrete experience” ([43], p. 12). It is “a purposive, planned selection, abstraction, combination, and (sometimes) accentuation of a set of criteria with empirical references that serves as a basis for comparison of empirical cases” ([43], p. 16). The words “selection,” “intensification,” and “accentuation” suggest that the type is constructed on the basis of selected features; and
often associated with qualitative data, we plan to follow an explanatory sequential casestudy research design where we pursue a rich description of two decades of data to betterunderstand the vertical transfer pathway into engineering degree programs [79]. By considering arich data source of background characteristics, enrollment patterns, and student outcomes over twodecades, this study also aims to contribute to the broader discourse on engineering education byinvestigating trends in vertical transfer student success at research-intensive institutions.3.1 Study Context and Data Source. This study used two decades of data from SU, a large publicresearch-intensive university in Florida. SU was chosen as the case study site due to its strong
AI/ML [63], CS support programs may be a promisingopportunity to further engage and motivate socially-oriented students in the field. As suggestedby previous work for AI/ML [64], retaining socially-oriented students may also promote genderdiversity since women show higher levels of ‘social benefit interest’ than their peers who do notidentify as women [63].While our study demonstrated that inspiration from instructors’ displays of support andenthusiasm for CS inspired students’ plan for social impact in CS, we also acknowledge that CSsupport programs have the potential to better address socially-oriented interests. This may beachieved by introducing students to speakers in CS backgrounds with obvious social impact,such as healthcare [64
inengineering. Al-Sanad and Koushki [31] and Aswad et al. [24] discuss the importance of policyinterventions in Qatar and the UAE. Mehran [39] highlights how institutional support andeducational reforms help in closing the gender gap. Using these policy interventions on a widerscale, despite creating more fair opportunities for women, will effectively increase the quality anddiversity of the engineering workforce. Implementing measures such as awarding scholarships,creating flexible programs and career promotion plans will encourage and support women topursue and succeed. In addition to achievement, the impact of such actions contributes to broadereconomic growth and innovation, as a diverse workforce is recognized as a key driver of creativityand