Scholarlink

<p>This study investigated the impact of a computer-based tutoring system, the Generalized Intelligent Framework for Tutoring (GIFT), on the cognitive achievements of senior high school students in Ghana studying Elective Information and Communication Technology (ICT). Conducted at a resource-constrained school newly equipped with a donated computer laboratory, the study employed a one-group pretest-posttest multiple-baseline quasi-experimental design. Thirty-five students completed four sequential lessons covering Python programming and computer software concepts. Standardized multiple-choice assessments, administered and graded within the GIFT platform, evaluated learning outcomes. Paired-samples t-tests revealed improvements in students’ posttest scores across both content areas. Normality tests confirmed the appropriateness of parametric analyses. Findings demonstrate the potential of structured self-directed digital instruction to enhance ICT education in settings traditionally limited by infrastructural challenges. The study contributes to the discourse on scalable, technology-enhanced learning solutions in low-resource educational environments and provides insights for future interventions using intelligent tutoring systems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Enhancing computing education and gender equity through the Generalized Intelligent Framework for Tutoring (GIFT) in a developing country

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月26日

查看全文
  • Emmanuel Okyere Ekwam,
  • Emmanuella Sefiamor Heloo,
  • Peter Akinsola Okebukola,
  • Felicia Nkrumah Kuagbedzi,
  • Adekunle Ibrahim Oladejo

摘要

This study investigated the impact of a computer-based tutoring system, the Generalized Intelligent Framework for Tutoring (GIFT), on the cognitive achievements of senior high school students in Ghana studying Elective Information and Communication Technology (ICT). Conducted at a resource-constrained school newly equipped with a donated computer laboratory, the study employed a one-group pretest-posttest multiple-baseline quasi-experimental design. Thirty-five students completed four sequential lessons covering Python programming and computer software concepts. Standardized multiple-choice assessments, administered and graded within the GIFT platform, evaluated learning outcomes. Paired-samples t-tests revealed improvements in students’ posttest scores across both content areas. Normality tests confirmed the appropriateness of parametric analyses. Findings demonstrate the potential of structured self-directed digital instruction to enhance ICT education in settings traditionally limited by infrastructural challenges. The study contributes to the discourse on scalable, technology-enhanced learning solutions in low-resource educational environments and provides insights for future interventions using intelligent tutoring systems.