Using the domain identification model to study major and career decision-making processes

Tendhar, Chosang; Singh, Kusum; Jones, Brett D.

doi:10.1080/03043797.2017.1329280

Cited by 18 publications

(14 citation statements)

References 27 publications

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“…A total of 32 TF and 48 SF from HSS participated in the online pilot testing conducted a month prior to general administration of the survey. Icelandic translation of the validated scale showed similar internal consistency to previously reported measures and all scales showed good or acceptable internal consistency with Cronbach's alpha (α), as reported in Table .…”

Section: Methodssupporting

confidence: 64%

Factors predicting identity as educators and openness to improve: an exploratory study

et al. 2019

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Context Researchers suggest that teachers’ work environment affects their sense of connectedness and appreciation, which affects their educator identity. However, sessional (also known as adjunct, clinical, contingent and non‐tenured) faculty members may struggle with their educator identity. The purpose of this exploratory study was to examine the extent to which perceived connectedness and received appreciation predicted identity as a medical (health care science) educator and openness to improve in tenure‐track and sessional faculty members. Methods We utilised an ‘identification with teaching’ scale to measure medical educator identity. We developed scales to measure perceived connectedness to university department, openness to improve teaching, and appreciation as a motivation to try a new teaching method. We then hypothesised a path model between these constructs. We surveyed faculty members at a health sciences school and performed confirmatory factor analyses and structural equation modelling using data from a sample of 73 tenure‐track and 146 sessional faculty members to explore support for the hypothesised model. Results Connectedness and appreciation predicted identity as a medical educator and openness to improve in different ways for sessional and tenure‐track faculty members. For tenure‐track faculty members, appreciation predicted medical educator identity and openness to improve, whereas a sense of connectedness trended towards predicting an openness to improve. For sessional faculty members, connectedness to their department predicted their identity as a medical educator, which acted as a mediator to predict an openness to improve. Discussion Our data supported the hypothesised model, but the sessional and tenure‐track faculty models differed in strength and focus. We explore reasons for these differences based on the working environment of each teacher type. We suggest that the two models partially explain the transformation from ‘a clinician who teaches’ to a medical educator. Finally, we make suggestions for how identity as a medical educator and openness to improve may be encouraged in both types of teachers.

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Section: Methodssupporting

confidence: 64%

Factors predicting identity as educators and openness to improve: an exploratory study

et al. 2019

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“…The complete MUSIC inventory is available online at Jones (12) and example items include the following: “I have flexibility in what I am allowed to do in this course” (empowerment), “In general, the coursework is useful to me” (usefulness), “I am confident that I can succeed in the coursework” (success), “The coursework is interesting to me” (interest), and “The instructors care about how well I do in this course” (caring). Researchers have found that the MUSIC Inventory is reliable and valid for use with many different types of students and courses (13, 14, 18).…”

Section: Methodsmentioning

confidence: 99%

“…Researchers have validated the College Student version of the MUSIC Inventory for use with undergraduate students in the U.S. (13, 14), China (15), Colombia (15), and Egypt (16). Less is known about the validity of the MUSIC Inventory when used for post-graduate students, such as those in professional schools.…”

Section: Introductionmentioning

confidence: 99%

Validation of the MUSIC Model of Academic Motivation Inventory: Evidence for Use With Veterinary Medicine Students

Jones

Byrnes

Jones³

2019

Front. Vet. Sci.

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The MUSIC® Model of Motivation is used to help instructors select strategies that can increase students' motivation and engagement in courses. The MUSIC model is comprised of five categories of strategies titled: empowerment, usefulness, success, interest, and caring. The purpose of this study was to examine the extent to which the MUSIC® Model of Academic Motivation Inventory (College Student version, short-form), demonstrates acceptable psychometric properties when used with students enrolled in a College of Veterinary Medicine. The inventory is comprised of five scales that correspond to the five MUSIC model components, and it measures the extent to which students perceive that: they have control in the course (empowerment); the activities in the course are useful to their future (usefulness); they can succeed in the course (success); the teaching activities and coursework are interesting (interest); and the instructor cares about students' learning and well-being (caring). The inventory has been validated for use with many different student populations, including students in different countries and of different ages (e.g., college students, middle and high school students, elementary school students). However, the inventory has not been validated for use with veterinary medicine students. We analyzed the data from 578 questionnaires that were obtained from students in six different courses at a College of Veterinary Medicine. We examined the psychometric properties of the MUSIC inventory by: (a) computing the internal consistency reliabilities for the scales; (b) calculating the fit indices and factor loadings obtained from confirmatory factor analyses; and (c) computing correlation coefficients between the inventory scales and students' self-reported effort in the course. The results provide evidence that the inventory demonstrates acceptable psychometric properties for use with veterinary medicine students. Consequently, the MUSIC Inventory can be used by researchers and instructors to assess students' motivation-related perceptions of courses.

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“…Of these identities, disciplinary engineering identity has been studied most extensively among engineering students. Studies of undergraduate engineering identity have demonstrated relationships between engineering identity and retention in engineering (Patrick et al, ; Pierrakos, Beam, Constantz, Johri, & Anderson, ; Tendhar et al, ) and science and math identity and pursuit of an engineering major (Godwin, Potvin, Hazari, & Lock, ). Other studies are also beginning to link identity to persistence among engineering doctoral students (Miller et al, ).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…A potentially productive perspective for understanding how engineering doctoral and master's students view different career preferences is engineering identity, or the degree to which an individual identifies with engineering (Eliot & Turns, ). At the undergraduate level, research has linked engineering, science and math identity to engineering persistence and career intentions (Godwin, ; Hazari, Sonnert, Sadler, & Shanahan, ; Patrick, Borrego, & Prybutok, ; Tendhar, Singh, & Jones, ). Other studies have demonstrated relationships between aspects of science or engineering identity and decisions to pursue graduate study (Borrego, Knight, Gibbs, & Crede, ; Estrada, Woodcock, Hernandez, & Schultz, ; Ro, Lattuca, & Alcott, ).…”

Section: Introductionmentioning

confidence: 99%

Master's and doctoral engineering students' interest in industry, academia, and government careers

Choe

Borrego

2020

J of Engineering Edu

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Background: Graduate education literature tends to focus on faculty careers with little attention to industry careers. However, more than one-third of U.S. engineering doctorates enter industry.Purpose: Our purpose is to understand engineering graduate students' interest in industry, academia, and government careers as it relates to their graduate engineering identities.Design/Method: A total of 249 engineering thesis master's and doctoral students completed a survey about their graduate engineering identities and career preferences. We created regression models to predict students' likelihood of pursuing careers in industry, academia, and government. Then, we used cluster analysis to understand the extent to which students are considering multiple options and used chi-squared and ANOVA tests to compare the clusters.Results: In the regression model predicting an academic career, research recognition and research performance/competence were positive predictors and engineering performance/competence was a negative predictor. Regression models of industry and government described less than 10% of the variance. Four clusters emerged, which collectively demonstrate that engineering graduate students are considering careers in multiple sectors. Students with internships during graduate study were more likely to pursue industry careers.Master's students were underrepresented in the cluster with highest likelihood of an academic career. International students were keeping more options open than some domestic students. There were also differences by engineering discipline. Conclusions: Engineering graduate students are considering multiple career sectors. Advisors and education researchers should focus not only on academic career preparation but also on industry and government career preparation, particularly on preparing for multiple options simultaneously. K E Y W O R D Scareer choice, master's students, PhD students, regression, survey

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Using the domain identification model to study major and career decision-making processes

Cited by 18 publications

References 27 publications

Factors predicting identity as educators and openness to improve: an exploratory study

Factors predicting identity as educators and openness to improve: an exploratory study

Validation of the MUSIC Model of Academic Motivation Inventory: Evidence for Use With Veterinary Medicine Students

Master's and doctoral engineering students' interest in industry, academia, and government careers

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