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Fields in the social sciences, such as education research, have started to expand the use of computer-based research methods to supplement traditional research approaches. Natural language processing techniques, such as topic modeling, may support qualitative data analysis by providing early categories that researchers may interpret and refine. This study contributes to this body of research and answers the following research questions: (RQ1) What is the relative coverage of the latent Dirichlet allocation (LDA) topic model and human coding in terms of the breadth of the topics/themes extracted from the text collection? (RQ2) What is the relative depth or level of detail among identified topics using LDA topic models and human coding approaches? A dataset of student reflections was qualitatively analyzed using LDA topic modeling and human coding approaches, and the results were compared. The findings suggest that topic models can provide reliable coverage and depth of themes present in a textual collection comparable to human coding but require manual interpretation of topics. The breadth and depth of human coding output is heavily dependent on the expertise of coders and the size of the collection; these factors are better handled in the topic modeling approach. 

Companies and their executives are concluding that to accomplish their complex tasks and all-encompassing missions and goals, they must step outside the traditional realms of teamwork and partnership and engage in cross-cultural and multinational alliances. One of the principal areas affecting teamwork today, especially in diverse workplaces, is the variety of cultural value orientations that the members relate to. To better prepare students for joining global enterprises, it is necessary to understand their cultural orientations and how those may influence their teamwork interactions. This study used a mixed methods design to characterize computer and information technology undergraduate students’ cultural orientations and their cultural awareness in the context of teamwork experiences. The data for the study was collected in the form of a reflection assignment that was implemented during the first week of classes as a way to promote students’ cultural awareness and how that may play out in their teamwork interactions. The reflection assignment had two parts: (i) a survey and (ii) reflection questions. The study used descriptive statistics and t-tests to analyze the survey (quantitative data), and thematic analysis was conducted to analyze the reflection questions (qualitative data). Our analysis of the quantitative data revealed that students identified the following core values they are Individualism, Equality, Monochronic, Meritocracy, Informality, Personal Efficacy, and Directness, and these values resonated with most of the students in class. Corresponding qualitative themes that emerged regarding students’ beliefs of how those values may play out in their teamwork experience were (a) Treating everyone equally and understanding others, (b) Increasing temporal Awareness, (c) Enacting effective communication, (d) Monitoring the progress of team members and (e) Establishing rules and boundaries. 

Commitment is a multi-dimensional construct that has been extensively researched in the context of organizations. Organizational and professional commitment have been positively associated with technical performance, client service, attention to detail, and degree of involvement with one’s job. However, there is a relative dearth of research in terms of team commitment, especially in educational settings. Teamwork is considered a 21stcentury skill and higher education institutions are focusing on helping students to develop teamwork skills by applied projects in the coursework. But studies have demonstrated that creating a team is not enough to help students build teamwork skills. Literature supports the use of team contracts to bolster commitment, among team members. However, the relationship between team contracts and team commitment has not been formally operationalized.This research category study presents a mixed-methods approach towards characterizing and operationalizing team commitment exhibited by students enrolled in a sophomore-level systems analysis and design course by analyzing team contracts and team retrospective reflections. The course covers concepts pertaining to information systems development and includes a semester-long team project where the students work together in four or five member teams to develop the project deliverables. The students have prior software development experiences through an introductory systems development course as well as multiple programming courses. The data for this study was collected through the team contracts signed by students belonging to one of the 23 teams of this course. The study aims to answer the following research question: How can team commitment be characterized in a sophomore-level system analysis and design course among the student teams?A rubric was developed to quantify the team commitment levels of students based on their responses on the team contracts. Students were classified as high or low commitment based on the rubric scores. The emergent themes of high and low commitment teams were also presented. The results indicated that the high commitment teams were focused on setting goals, effective communication, and having mechanisms in place for timely feedback and improvement. On the other hand, low commitment teams did not articulate the goals of the project, they demonstrated a lack of dedication for attending team meetings regularly, working as a team, and had a lack of proper coordination while working together. 

Information technology professionals are required to possess both technical and professional skills while functioning in teams. Higher education institutions are promoting teamwork by engaging students in cooperative and project-based learning environments. We characterized teams based on their collective orientations and evaluated their team performance in a cooperative project-based learning environment situated in a sophomore-level systems analysis and design course. We explored the orientation patterns in terms of goals, roles, processes, and interpersonal relations (GRPI). Specifically, we analyzed team retrospectives of 23 teams using a mixed-method approach. Findings characterized teams into balanced and unbalanced orientations. Teams with balanced orientations demonstrated a higher level of team performance in terms of academic achievement than the unbalanced category.