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Dispositions are valued by employers and promoted by recent computing curricular recommendations. Yet, fostering and assessing dispositions are not well understood. In a multi-institutional study, students were asked to assess their dispositions in terms of behaviors that were identified in prior literature for those dispositions, both at the start and the end of a term. During the term, instruments were used to have students reflect on their dispositions. The research questions of the study are: 1) Do students associate behaviors with the dispositions for which they were identified in prior work? 2) Does reflecting on dispositions change how students assess themselves in terms of the behaviors? and 3) Is there a difference between introductory and upper-level students in how they assess themselves in terms of the behaviors? The findings of the study are that 1) at least 60% of the students associated the behavior statements with the dispositions for which they were identified; 2) students lowered their self-assessment of some behaviors after reflecting on dispositions; and 3) upper-level students assessed themselves more positively on some behaviors than introductory students. These results support a model of development of dispositions in which self-assessment of behaviors associated with dispositions improves with academic level, but at each level, gets revised lower after reflection. 

Lifelong learning is essential in computing, given the dynamic nature of the field. Employers and curricular reviewers recognize the value of being self-directed in support of becoming a lifelong learner. The ACM/IEEE-CS Computing Curricula 2020 report identifies self-directed as having elements of self-motivation, determination, and independence. Little is known, however, about how to cultivate this disposition in computing courses. The motivation of this study is to better understand what behaviors computing students believe are self-directed. This study’s research questions are: 1) What do students describe as their self-directed practices in computing? and 2) What do students report are factors that prevent them from being self-directed? Assignments in five undergraduate computing courses from four institutions included prompts to elicit student’s reflections on how they were self-directed (or not). Thematic content analysis using the constant comparative method produced eight categories of self-directed behaviors (utilizing external resources, learning necessary material, working independently, assessing oneself, planning ahead, applying useful techniques, completing the assigned work, and reviewing against expectations). Thematic analysis also resulted in five categories of factors that impeded the self-directed behavior (assignment structure, unsuccessful effort, self-sufficiency, insufficient motivation, and insufficient time). Understanding how students describe self-directedness can help educators design pedagogical and assessment approaches that facilitate self-directed student behaviors in the classroom. 

This full research paper contributes to current work on fostering professional dispositions in computing and engineering education by identifying the categories of behaviors that students associate with dispositions while doing course work. Professional dispositions, demonstrated through desirable behaviors in the workplace, such as being persistent or self-directed, are explicitly sought by employers. Fostering dispositions among students has been identified in various curricular recommendations as an important goal. In prior work, the authors used reflection exercises, in which students were presented with the definition of a disposition and asked to answer an open-ended reflection prompt on how they applied the disposition in their own work. Thematic analysis of student responses to reflection exercises resulted in categories of behaviors that students associated with dispositions. In the work discussed in this paper, the authors used vignette exercises to collect and analyze similar data and gain further insight into behavioral categories and students’ perceptions of dispositions. Vignettes include short scenarios that demonstrate the application of dispositions in real life. A vignette exercise involves students reading a vignette scenario, identifying the disposition demonstrated by the scenario, and answering the same open-ended reflection prompt as in the reflection exercises from the earlier studies. The research question for this study is: Which behavioral categories obtained from analyzing student responses to reflection exercises were confirmed using vignette exercises (and which were not confirmed), and which behavioral categories were refined? To answer this question, researchers from four different institutions of higher education collected data in multiple courses over two semesters. The student open-ended responses to vignettes were thematically analyzed to identify behavioral categories for four dispositions: collaborative, meticulous, persistent and self-directed. The ultimate goal of this work is to create classroom interventions and learning activities that foster dispositions among students based on behavioral categories. This study supports this goal in two ways. It provides another iteration of behavioral category analysis and introduces vignettes to encourage students to reflect candidly and communicate clearly how they apply dispositions in terms of behaviors. The study results and their implications for fostering dispositions in a classroom setting are presented and discussed. 

Dispositions, skills, and knowledge form the three components of competency-based education. Moreover, dispositions are considered crucial for students to succeed in the workplace. Few studies investigate how dispositions manifest in the form of observable behaviors, which causes challenges for both students and educators. Computing students, for example, may not understand what is expected of them, and how to achieve dispositions. This paper presents the results of a qualitative, multi-institutional study on students’ understanding of the dispositions adaptable, persistent, self-directed, meticulous, and professional. Perceptions were gathered by asking for exemplary situations of students applying each of the five dispositions in the context of assignments within computing courses. Students who indicated they did not apply the disposition were asked to describe the hindering circumstances. The data was evaluated by using Mayring’s content analysis technique, resulting in the development of deductive-inductive categories of observable behaviors reflecting the student’s perspective. For meticulous and professional, new categories representing observable behaviors were developed. For adaptable, persistent, and self-directed, the authors confirmed and extended prior work. Moreover, factors hindering students in applying the investigated dispositions are identified. The resulting categories with observable student behaviors are an important step toward the operationalization of competency-based learning outcomes including dispositions. A common understanding of dispositions will also help with the design of new forms of instruction and measures to foster the application of dispositions in the context of computing education. 

Competencies are knowledge, skills, and dispositions that enable professionals to successfully perform a goal-oriented task. A traditional education model focuses primarily on presenting and assessing knowledge, with student performance represented by grades. The Competency-Based Education (CBE) model focuses on each student developing and demonstrating knowledge, skills, and dispositions. This implies a difference in the approach towards curriculum (content), pedagogy (teaching methods), and assessment. This workshop will introduce basic concepts of competencies and CBE. We will present a competency list derived from research on computing professionals' experiences. Participants will develop a spiral curriculum and (re)design a course to purposefully integrate cross-disciplinary skills (e.g., communication) and dispositions (e.g., perseverance), along with computing skills. Takeaways will include: (1) an understanding of what competencies and CBE are, and what pedagogical and assessment approaches may align with CBE; (2) a document that integrates competencies across a spiral curriculum; and (3) a plan for (re)designing one of their courses. Collaborative ideation will be used to help generate ideas for each participant's unique context and goals. Higher education faculty/instructors and administrators who would like to learn more about competencies and apply CBE practices to their own program/course will find the most benefit from this workshop. Multiple people from the same program are encouraged to attend, allowing them to consider how they can plan for integrating competencies across their program-level curriculum. Please bring internet-enabled laptops/comparably sized devices, choose a course to (re)design, and have access to relevant course materials. 

The release of the Information Technology (IT) 2017 curricular guidelines provided the impetus to focus on students’ professional competencies by incorporating authentic practice into disciplinary content. Authentic practices require appropriate learning experiences such as workplace-bound experiences, employer engagement with programs via paid internships, and critical reflection on what was learned. Both professional technical and non-technical skills must be emphasized for such authenticity. However, practical assessment of the learning of professional competencies remains challenging. This paper develops such a practical assessment approach to IT competencies. It builds on the industry-led Skills Framework for the Information Age (SFIA) that defines over 120 IT professional skills across seven levels of responsibility and experience. SFIA provides actionable and measurable activities and behaviors, which IT graduates need to demonstrate in the workplace. The paper explores the assessment of student performance on authentic, real-world tasks using a rubric-based scoring scheme supported by a systematic collection of sample student work over their time in the program. It concludes with a discussion of the validation of the proposed approach to demonstrate its practicality.