research team we document our positionality.The research team consists of members with a wide range of political views (consisting ofregistered democrats, republicans, and independents) and demographic diversity (including butnot limited to individuals who identify as mixed race, White, male, female, cisgender, gay, andstraight). All members of the research team had an interest in understanding and improving theexperiences of diverse individuals in engineering. Prior to conducting the interviews, the entireresearch team documented and discussed their positionality so as to understand the ways inwhich their position as a researcher could influence the interview and analytic processes.During the interview, participants were asked to reflect on the
within a specific discipline. No matter which instrumentresearchers have adopted, measures of the multidimensional framework have been problematicin terms of validity and reliability. For example, some of the theoretical factors were notidentified in some studies [8], [9], and some researchers have found the factor structures are hardto duplicate in replicated studies [10]. Therefore, existing instruments may be inadequate to capture the representations ofengineering students’ domain-specific epistemic beliefs. The first explanation of theseassessment-issues is the predefined meanings within the questionnaires [11]. Although one mayargue that the theorized meanings reflect the overarching framework of key components ofepistemic beliefs
educational experiences from an MI viewpoint. This includesan assessment of the current status of MI presence in the undergraduate engineering curriculumand the extent to which it should be.MethodologyA total of 210 senior engineering students have participated in the study, of which 85.3% were inthe 18 – 25 year age group and 66.2% were male. Seniors were selected since the study focuseson undergraduate education and seniors would presumably be in the best position to reflect ontheir educational experiences from initial entry into engineering up to the final undergraduateyear. A Qualtrics survey instrument was developed that probed: 1) self-perception of the extentto which the student had any characteristics of each MI; 2) the student’s perception
Illinois at Chicago B.S. Purdue University c American Society for Engineering Education, 2016 Continuous Evaluation of Student Class Performance Using Group Based, In-class QuizzesIntroductionTraditional methods of evaluating student performance in the classroom involve assigningweekly homework assignments, semester long projects, conducting examinations (e.g., mid-terms/finals), and holding arbitrary pop quizzes. Amongst these methods homework assignmentsare a traditional indicator of a student’s continuous learning of the subject matter. Traditionally,performance on homework assignments reflects the level of understanding that the student has ofthe material that is covered in the
and the orientation todesign and delivery in this course are based on the online Community of Inquiry model(Garrison, Anderson & Archer, 20013; Vaughan, Cleveland-Innes, & Garrison, 201314). Thismodel is based on Dewey’s (1910)15 views on experiential learning and is constructivist innature. The role of instructor and student are transformed by three overlapping presences:cognitive, social, and teaching presence. Social presence is defined as the extent to whichlearners are socially and emotionally connected with others in an online environment; cognitivepresence describes the degree to which learners are able to construct and confirm meaningthrough sustained reflection and discourse. The central organizing element is teaching
creativity between males andfemales.12 For instance, Felder, Felder, Mauney, Hamrin, & Dietz13 found that female studentsdesired and expected more creative work at the start of engineering courses than males, but ratedtheir own creative problem solving ability significantly lower than males at the end of the course.However, the self-ratings may not have accurately reflected performance on these tasks. Inanother study, Charyton & Merrill11 found that female engineering students actually scoredhigher on post-test creative design tasks than males even though there were no genderdifferences in creativity at the beginning of the activity. The results from these studies indicatethat engineering courses and programs may influence the perception of
science [16, 17] but found that they focus on principles and conceptsthat reflect the deep understanding of expert computer scientists [9]. The need remains to bettercharacterize the computational competencies as applied in the context of the engineering practice. A major effort during CPACE II —and the subject of this paper—is to determine students’computational skills and capabilities while solving engineering problems. The guiding researchquestion is: what are the features that broadly characterize the knowledge, skills and behaviorsassociated with computational competencies for undergraduate engineering students? A major challenge emerged during our initial analyses of student artifacts using the CPACEcomputational competencies framework
identified.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.1361417. Any opinions, findings and conclusions, or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References1. Borrego, M., Froyd, J. E., & Hall, T. S. (2010). Diffusion of Engineering Education Innovations: A Survey of Awareness and Adoption Rates in U.S. Engineering Departments. Journal of Engineering Education, 99(3), 185-207.2. Hall, G., & Hord, S. (1987). Change in Schools: Facilitating the Process: State University of New York Press.3. Hall, G. E., & Hord, S. M. (2006). Implementing change: Patterns, principles, and
materials. Roughly 56% indicated the same for the associated quiz. When comparedwith other active learning activities in the class, 100% of the students indicated that the debatesbetween students on concepts covered in the classroom were either effective or very effective inlearning the concepts covered in the class. In addition, 89% of students indicated that the caseanalysis and discussion were effective or very effective. These responses are also reflected inFigure 2, where the aforementioned activities are ranked higher than the quiz with studentcreated questions which students indicated are as useful as the lecture. On closer examination,feedback from students indicated that they felt that more time was needed to complete thisactivity
are used by teachers (described in the next section). Using text from scales of engineeringself-efficacy and interest, we reflect on the pedagogical strategies for enhancing studentconfidence and interest which emerge from the lesson content. Then, as a second method forevaluating the impact of our lessons, we map changes in student self-efficacy and interest scoresreported before and after the soft robotics lessons. According to Wickham and Grolemund [18],these exploratory approaches offer insight that is not otherwise obtained. Along with morestructured statistical analysis which we have reported elsewhere, the content analysis andcharacterization of changes in student perceptions support the refinement of the curriculummoving forward.Soft
, collaborative, Employ various group Utilize learning exercises, and reflective activities to activities throughout lectures small projects, and group lectures discussions in lecture Purpose Engage students Engage students Engage students Support active and social Support active learning Support active and social learning Encourage attendance learning Example(s) Create a jigsaw activity for a Split class into sections, each Flip classroom challenging class topic working on
. This conflation of moments and rotationsmight reflect “inappropriate groupings” or overly simple causal narratives created by studentslike those described in [12]. Even Jasmine, who provided the correct definition of momentconsistently, struggled with its relationship to rotation. Further analysis of the full interviewsmay help provide clarification of the type of misconception as well as factors that influence itsdevelopment or reinforcement. For example, Kayla mentions that the terms are “usually in thesame sentence” when discussed in class, leading her to see them as the same. Thus, themisconception might be reinforced by analogies typically used in instruction. The effects of thismisconception on course performance might also be
also adapted Ashford and Blacks [7] scales measuring proactive behaviors across six dimensions: (a) feedback seeking, (b) positive framing, (c) general socializing, (d) relationship building, (e) networking, and (f) information seeking [7]. Though these scales were developed to understand workplace socialization, we adapted them to reflect the context of engineering education. Then, to assess normative contexts, we developed a new five-question scale to explore students’ involvement in extra- and co-curricular activities. First, we ask students to list engineering-related organizations in which they participated. Second, and germane to the concept of socialization, we ask how students
signify the unification of cognitive elements of self-motivation, self-direction, self-reflection, self-regulation, and self-correction.and interactive virtual environments (VEs) [17],[33],[34]. Thereby multiple approaches may becombined to enhance the user experience and increase the learning success. For example, asituation-based gaming environment may allow learners to explore content on their own, thus,increasing their sense of autonomy and progress control, factors identified as important to learnerself-regulation and responsibility [11],[13],[24],[29],[35].Through VEs users can be immersed in specific environments in order to elicit tasks under whatis perceived as realistic circumstances. Thus, fidelity as “a measure of the degree to which
International Civil Aviation Organization (ICAO) emphasized the critical nature ofempowered, autonomous individuals and work teams as success factors in global aviation safetyand process standardization [60], [61] applicable to all of the aviation industry [6], [61]. Self-responsibility and proactive problem-solving expectations are likewise modeled by the FAA inits relationship with industry in safety and quality management of daily processes [4]. Problem-based learning in engineering was consistently emphasized in preparing engineering graduates,and development of collaborative teamwork, self-directed, independent learning and problemsolving based upon critical self-reflection were considered “crucial competencies” in addition totechnical degree
participants’ability to recall detailed information about their interaction and resource usage after the fact. Inaddition, although survey questions asked participants to identify time spent interacting witheach peer in their network, few students gave such detailed descriptions. Lack of detailedresponses limited development of the peer interaction networks. For those participants whochose to provide only their names on surveys (presumably for the purposes of receiving extracredit), their responses were removed from data. FINDINGS AND DISCUSSIONSixty-six of 118 (56%) students enrolled in the course participated in all surveys. Participantdemographics are shown in Table 1. Participant demographics reflect the larger
shows that an engineering degree prepares students for a range of careers. However,engineering undergraduate training has often focused on equipping students with the knowledge,abilities, and attitudes that will make them successful as engineers in industry rather than the broadpossibilities that an engineering degree offers. Reflecting this focus, a common topic inengineering education literature discusses ways to bridge the gap between industry andundergraduate training [1]. However, the qualities students develop—such as critical thinking,problem solving, and teamwork—are also valued by employers in general. Additionally, researchstudies in engineering education on students’ post-graduation pathways often frame students whodo not enter
“multidisciplinary perspective” to systems thinking – one that equips students not only toaddress technical problems but to communicate the value of ethical, persuasive decision-makingin the workplace [1]. Yet, as the Boeing report suggests, “major opportunities for reform existbut have yet to be exploited” [1]. Among these curricular reforms yet to be exploited is the move“from the stage of dumping ‘expert-recommended’ communication strategies to the stage oftailoring communication strategies to achieve clarity of understanding with different audiences”[1]. This call for curricular reform is also reflected in the most recent update to the AccreditationBoard for Engineering and Technology, Inc. (ABET) outcomes for engineering programs, whichrequires that
to which I have no idea what I'm doing like 95% of the time.”—Amy (fifth year graduate student)Attitudes towards ExpectationsTo add insight to this data, we also characterized the interview excerpts that discussed expectationsunder one of four categories, deemed “expectation attitudes:” Correct and Positive, Correct andNegative, Incorrect and Positive, and Incorrect and Negative. From the interviews, we determinedwhether their expectations of graduate school were proven correct or incorrect. It is important tonote that these labels do not define what is “right” about the expectation (e.g., the expectation ofgraduate school being coursework heavy, for example, which is generally not reflective of doctoralengineering culture, was not
systematic set of procedures to develop an inductivelyderived grounded theory about a phenomenon" [25, p.24]. The five processes of modifiedanalytic induction (mentioned above) reflect the systematic set of procedures within thegrounded theory paradigm.Collecting and coding the material constituted step one of the constant comparative analysis.Codes are abbreviations or symbols applied to a segment of words to facilitate sorting andclustering word segments relating to a particular topic or question [23]. Using the guidingquestions, the first author developed categories of information (open coding). In the open codingphase, the first author examined the textual and visual information (transcripts and drawings) forsalient categories of information
solve this problem? How do you use your theoretical principles or laws? Problem solving Should you expect to get these answers? Problem solving How can you check your answers? Quick reflections Based on your self-evaluation, what are your weak Quick reflections areas?3. Insight into Self-Regulated LearningZimmerman argued that self-regulated learners are “metacognitively, motivationally, andbehaviorally active participants in their own learning process”19, p. 239. It is clear thatmetacognition is a major component of one’s self-regulated learning (SRL) strategies. In thisarticle we used SRL processes to represent the link between metacognition and SRL
dictates theinteraction of students with the material and each other so as to increase their learning.In contrast, active learning has been described as the process by which students engage inactivities which causes them to reflect on their own learning [5]. Students are thereby forced tothink about how their level of participation or contribution to the learning process affords themthe ability to improve their mental and physical learning of the concept in a desired manner. Inthis student-centred approach to instruction, the instructor provides students with the opportunityto engage actively while learning independently from one another through the gathering ofinformation, thinking and problem-solving activities they are expected to complete
how those attitudes may reflect the choice of major.Engineering Students at the University of San DiegoAt many universities, students apply to a specific major, and the admission criteria may changewith the major. Furthermore, enrollments in some majors may be capped. In these cases, highschool performance, or SAT or ACT scores are often used to determine which students areadmitted. Where engineering programs have restricted admissions, this can mean that studentswith high grades and test scores, but modest aspirations to become engineers may be admittedover highly motivated students with lesser academic credentials. While the characteristics ofstudents in the differing programs can be compared, the differences that are identified
, and skills on a scalethat will meet the need. Although some traditional engineering faculty workshops havehad positive results as reported by Felder and his colleagues, 2, 7, 8 several investigatorshave identified some important issues with the short-term, face-to-face model. 6, 9, 13Specifically, such workshops do not allow time for faculty members to go through thetransitions from awareness to action, 9 can cause an adversarial relationship between thepresenter and the participants, 6 and do not encourage participants’ motivation andcommitment.13 The inadequacy of existing faculty development models is reflected in: 1)the slow adoption of engaging, active-learning methods that have been systematicallytested and shown to improve student
. Constructivism, the perspective used by this study, embracesthe idea that the participants can actively make meaning of their various critical experiences withfamily members and relate how those experiences influenced their academic decisions aboutengineering.17Methodology Once the research questions were formed, a methodology was selected. Strauss andCorbin state that qualitative methods can be used to better understand any phenomenon aboutwhich little is yet known.18 FGC students, especially those majoring in engineering, are not wellstudied and are known to face unique academic challenges.19 Further, qualitative studies yieldresults that are reflective of the descriptive experiences and feelings of the participants.20 To better
metaphors fit or do notfit their career experiences. We ask new faculty to reflect on their interviewing and hiringexperiences, look ahead to their third-year reviews, discuss their departments’ workingatmosphere, and reflect on their interviewing and hiring processes. We ask third-year faculty toreflect on their interviewing and hiring experiences, their experiences as faculty at their currentuniversity, and satisfaction with their productivity and accomplishments in their careers so far.Additionally, we ask third-year faculty to discuss what they feel their next professionalaccomplishments will be. All interviews conclude with general career path reflections.Data collectionData are collected for research conducted for an ADVANCE grant, a National
productivity.Professional Development: 5. Growth Planning (F) Individuals document professionalIndividual demonstration of 6. Growth Progress (F) development in technical,improved knowledge, skills, 7. Professional Practices (F) interpersonal, and individualand behaviors essential to 8. Growth Achieved (S) attributes important to their personalengineering practice and project needs, professional behaviors, and ways of a reflective practitioner.Design Processes
under theumbrella of sustainable engineering. Page 22.418.2In this paper, we present two sets of data: (1) a comparative analysis of fifteen published sets ofsustainability principles (some of which are drawn from the context of engineering, some fromother contexts, but none in the context of engineering education), and (2) a summary of arepresentative set of engineering courses at US Universities that include sustainability terms intheir titles or course descriptions. While other methods of data collection may reflect a morenuanced understanding of the idea of sustainable engineering (and, in fact, seeking this nuance ispart of the motivation
requirements. 4 The writer addresses each aspect of the assignment. The writer addresses and develops each aspect of the assignment and goes 5 beyond the assignment prompt to address additional related material.For each of the 16 traits listed in Table 1 a score of 1-5 is given according to the level ofthe writing. From Table 2 it shows that a score of 5 reflects writing that exhibits keyunderstanding of the writing assignment while that of 1 is for work that does not addressthe requirements of the assignment. Thus the assigned level is the score for the trait andthis is done in 0.5 level increments. This is the scoring used by instructors to obtainresults shown below in Tables 4 and 5.Flateby and Fehr1 report that CLAQWA
example, Lutz(2017)found that thelearning experience of professional engineers occurred mostly through typical tasksrather than systematic learning methods[19]. Davis &Vinson(2017)explored theinteraction between senior engineers and novice engineers, and pointed out that theguidance provided by mentors was often formalistic instead of valuable [20]. Korte(2009) concluded that the establishment of interpersonal relationship is the key forindividual to quickly learn something and to integrate into the organization [21].Moreover, reflective discussions were also an important learning method whenengineers could not fully map the current problems to existing technical models [18],[22].Theoretical framework Cognitive apprenticeship is a