“It Was Horrible!” Understanding the Transition Experiences of Direct Year 2 Entry Students in Computer Science

While first-year transitions are well studied, less is known about students who enter directly into Year 2 of a four-year Scottish Computing Science degree via international foundation programmes, UK colleges, or high schools. This study investigated their academic preparedness, use of AI tools, English language confidence, and transition challenges. Using a mixed-methods design, 77 students completed a survey with Likert-scale and open-ended items. Findings indicate gaps in programming skills, independent learning, and understanding academic expectations. Many students reported feeling a sense of low social belonging after joining pre-established cohorts. AI tools were commonly used for programming support and concept clarification, but they offered limited emotional reassurance. Students recommended clearer academic alignment, a tailored induction process, compulsory social events, and peer mentoring. This study advocates for equity-driven transition models that cater to the diverse needs of direct entrants, thereby fostering inclusion, belonging, and success.

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Publication Details

Journal
Trends in Higher Education
Published
2025-10-08
DOI
https://doi.org/10.3390/higheredu4040057
Primary Topic
Higher Education and Employability
Type
article
Field-Weighted Citation Impact
0.00

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article

“It Was Horrible!” Understanding the Transition Experiences of Direct Year 2 Entry Students in Computer Science

Mireilla Bikanga Ada
Trends in Higher Education
Higher Education and Employability
article

“It Was Horrible!” Understanding the Transition Experiences of Direct Year 2 Entry Students in Computer Science

Mireilla Bikanga Ada
article en

Abstract

While first-year transitions are well studied, less is known about students who enter directly into Year 2 of a four-year Scottish Computing Science degree via international foundation programmes, UK colleges, or high schools. This study investigated their academic preparedness, use of AI tools, English language confidence, and transition challenges. Using a mixed-methods design, 77 students completed a survey with Likert-scale and open-ended items. Findings indicate gaps in programming skills, independent learning, and understanding academic expectations. Many students reported feeling a sense of low social belonging after joining pre-established cohorts. AI tools were commonly used for programming support and concept clarification, but they offered limited emotional reassurance. Students recommended clearer academic alignment, a tailored induction process, compulsory social events, and peer mentoring. This study advocates for equity-driven transition models that cater to the diverse needs of direct entrants, thereby fostering inclusion, belonging, and success.

Trends in Higher EducationVol. 4(4)
University of Glasgow (GB)
College of Science and Engineering, University of Minnesota
Openalex Percentile: Top 69%
Higher Education and Employability
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