A. Alhur, Arwa Alhur, Afrah Alhur, Kholod Almalki, Reem Aljoudi, Huda Aloqla, Sara AlKayyal, Mona Almalki, Anoud Alenazi, Aseel Almalki
{"title":"Evaluating Computer Science Students' Experiences and Motivation Towards Learning Artificial Intelligence","authors":"A. Alhur, Arwa Alhur, Afrah Alhur, Kholod Almalki, Reem Aljoudi, Huda Aloqla, Sara AlKayyal, Mona Almalki, Anoud Alenazi, Aseel Almalki","doi":"10.32996/bjtep.2023.2.3.5","DOIUrl":null,"url":null,"abstract":"This study investigates the experiences and motivations of Saudi Arabian computer science students (aged 18 and above) in their pursuit of knowledge in Artificial Intelligence (AI). It employs a cross-sectional design using web-based surveys. Findings indicate that students recognize AI's transformative potential in computer science and express a willingness to embrace it in their careers. However, confidence levels vary regarding using AI tools, understanding healthcare AI, and assessing AI's impact on computer science education. The study emphasizes the significance of intrinsic motivation, experiential learning, and pedagogical strategies like collaborative learning in AI education. Additionally, it underscores the importance of addressing gender and diversity considerations to create inclusive AI learning environments. In conclusion, this research provides valuable insights into computer science students' experiences and motivations in AI education. It offers practical implications for enhancing AI pedagogy, reducing barriers to learning, and promoting diversity and inclusivity in the AI field. Educators can empower students to navigate the dynamic AI landscape effectively by tailoring educational approaches to individual learner needs.","PeriodicalId":268908,"journal":{"name":"British Journal of Teacher Education and Pedagogy","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Teacher Education and Pedagogy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32996/bjtep.2023.2.3.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates the experiences and motivations of Saudi Arabian computer science students (aged 18 and above) in their pursuit of knowledge in Artificial Intelligence (AI). It employs a cross-sectional design using web-based surveys. Findings indicate that students recognize AI's transformative potential in computer science and express a willingness to embrace it in their careers. However, confidence levels vary regarding using AI tools, understanding healthcare AI, and assessing AI's impact on computer science education. The study emphasizes the significance of intrinsic motivation, experiential learning, and pedagogical strategies like collaborative learning in AI education. Additionally, it underscores the importance of addressing gender and diversity considerations to create inclusive AI learning environments. In conclusion, this research provides valuable insights into computer science students' experiences and motivations in AI education. It offers practical implications for enhancing AI pedagogy, reducing barriers to learning, and promoting diversity and inclusivity in the AI field. Educators can empower students to navigate the dynamic AI landscape effectively by tailoring educational approaches to individual learner needs.