An Analysis of the Effective Factors in Students' Academic Decisions with a Cognitive Approach (case study: Tehran University Students)

Objective: Students make many academic decisions during their academic careers, and these decisions are influenced by many internal and external factors. These decisions have significant consequences on their future education, careers, and personal lives. Knowing the reasons behind academic decisions can help improve students' academic success. Additionally, it has helped universities and higher education institutions achieve their goals, thus promoting the development of higher education. Another important point is the method of analyzing students' academic decisions with classical, neoclassical, behavioral and cognitive approaches. Each of these approaches has a specific look at decision-making based on the evolution of the newest and most complete cognitive approach. Therefore, the analysis of students' academic decisions with a cognitive approach will lead to more noteworthy achievements. Based on this, the purpose of this research is to categorize and prioritize the effective factors in students' academic decisions with a cognitive approach. To achieve this goal, two questions were designed; (a) According to the cognitive decision-making model, what components do students' academic decisions include? (b) Which component of the cognitive decision-making model has more weight and priority in the academic decisions of Tehran University students?
Materials and Methods: This research was conducted in two stages. In the first stage using the qualitative content analysis method of 50 graduate students from fourteen faculties at Tehran University who had made academic decisions during the period (1395-1400) using the purposeful random sampling method. The purposeful selection of samples is based on statistical analysis. We conducted interviews with these selected students. To analyze the data, specifically, the three-step approach of Elo and Kyngäs (2008) has been used. Based on this approach, the first step is choosing the unit of analysis and understanding and insight from the entire data; The second stage was organizing and the third stage was reporting the results. In addition, we used a cognitive decision-making framework (Naderi, 2013). This framework was the basis for designing interview questions and categorizing content analysis results. The mentioned framework had 9 components in different layers. In the second part, we prioritized educational decisions using Shannon's entropy analytical technique. Academic decisions in this research include the decision to leave, remove a semester, change fields, transfer, and drop out.
Discussion and Conclusion: In general, we identified 9 categories, 21 subcategories, and 600 key concepts. These components encompass thoughts and perceptions (personal thoughts and perceptions); preferences (personal preferences/preferences and non-personal preferences/preferences); values and emotions (individual values and emotions and impersonal values and emotions); environment and conditions (scientific environment (university) and social and cultural conditions); information and knowledge (personal information knowledge and non-personal information knowledge); risk and uncertainty (risk and ambiguity in conditions); institutions and governments (university level, higher education level, education level, government level, and military service level); consequences and results (individual consequences and results, non-individual consequences and results) and opportunities (individual opportunities and non-individual opportunities). Based on the weighting of these components, the most important ones are information and knowledge and risk and uncertainty. Essentially, we categorized and analyzed the extracted concepts based on the cognitive decision-making model. In the end, based on the research findings, policy proposals were presented for decision makers in higher education at two levels (micro and macro). Among the micro-level suggestions, we can mention the diversification of the financial aid and student loan systems to prevent students with lower economic levels from dropping out with timely measures. At the macro level, it is also possible to mention the proposal to develop the relationship between universities and industry and improve the labor market situation of graduates in order to prevent them from deciding to emigrate by creating more job opportunities for students in addition to their individual growth.