Selecting Suitable Programming Languages for Beginner-Level Instruction
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| Title: | Selecting Suitable Programming Languages for Beginner-Level Instruction |
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| Language: | English |
| Authors: | Adaiti Allen Kadams (ORCID |
| Source: | International Journal of Technology in Education and Science. 2026 10(1):133-161. |
| Availability: | International Society for Technology, Education, and Science. e-mail: ijtesoffice@gmail.com; Web site: http://www.ijtes.net |
| Peer Reviewed: | Y |
| Page Count: | 29 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Programming Languages, Foreign Countries, Technology Uses in Education, Usability, Value Judgment, Social Influences, Job Skills, Student Attitudes, Undergraduate Students, Preferences, Predictor Variables |
| Geographic Terms: | Nigeria |
| ISSN: | 2651-5369 |
| Abstract: | This study examines factors influencing the preference for Python and Java as introductory programming languages in a Nigerian higher education institution. Using an integrated framework combining the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Technology Acceptance Model (TAM2), key constructs such as perceived usefulness, ease of learning, social influence, and industry relevance were identified as crucial in shaping students' preferences. A survey of 308 second-year students revealed Python as the preferred beginner-level language, with 75.6% favoring it over Java. Python's perceived ease of learning (M = 4.09), usefulness (M = 4.41), and alignment with industry demands (M = 4.34) were significantly higher than Java's (M = 3.31, 3.74, and 3.78 respectively). Additionally, 70 students (over 22%) selected C++ as the best alternative, appreciating its ability to provide a deeper understanding of system-level programming. Regression analysis showed perceived usefulness ([beta] = 0.24), ease of learning ([beta] = 0.22), and industry relevance ([beta] = 0.21) as strong predictors of language preference, especially for Python. Students' perceptions of future use and social influence also significantly predicted preferences, highlighting Python's applicability to emerging technologies and career goals. The study recommends prioritizing Python for introductory courses, retaining Java for advanced topics, and integrating Generative AI tools to enhance programming education outcomes. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1494432 |
| Database: | ERIC |
| Abstract: | This study examines factors influencing the preference for Python and Java as introductory programming languages in a Nigerian higher education institution. Using an integrated framework combining the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Technology Acceptance Model (TAM2), key constructs such as perceived usefulness, ease of learning, social influence, and industry relevance were identified as crucial in shaping students' preferences. A survey of 308 second-year students revealed Python as the preferred beginner-level language, with 75.6% favoring it over Java. Python's perceived ease of learning (M = 4.09), usefulness (M = 4.41), and alignment with industry demands (M = 4.34) were significantly higher than Java's (M = 3.31, 3.74, and 3.78 respectively). Additionally, 70 students (over 22%) selected C++ as the best alternative, appreciating its ability to provide a deeper understanding of system-level programming. Regression analysis showed perceived usefulness ([beta] = 0.24), ease of learning ([beta] = 0.22), and industry relevance ([beta] = 0.21) as strong predictors of language preference, especially for Python. Students' perceptions of future use and social influence also significantly predicted preferences, highlighting Python's applicability to emerging technologies and career goals. The study recommends prioritizing Python for introductory courses, retaining Java for advanced topics, and integrating Generative AI tools to enhance programming education outcomes. |
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| ISSN: | 2651-5369 |
