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Lecturers perceptions of using Artificial Intelligence in Tertiary Education in Uzbekistan

Sedigheh Shakib Kotamjani, Sojida Shirinova, Mehrnaz Fahimirad

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Abstract

Artificial intelligence (AI) has revolutionized different aspects of society, including higher education. This paper investigates faculty members' perceptions of using artificial intelligence, chatbots, and generative AI in teaching and learning in Uzbeki's higher education contexts. The researchers employed a qualitative study using semi-structured interviews to collect the data. Purposeful sampling was employed to select participants in this study, and the interviews were conducted face-to-face at the university campus. The study's underlying theory is the Unified Theory of Acceptance and Use of Technology (UTAUT) model, including effort expectancy, performance expectancy, social influence, and facilitating conditions, which were employed as a lens to direct the research. The data were transcribed and analyzed using the deductive approach for the thematic analysis. The findings revealed that lecturers have a positive attitude to adopt and use AI for content creation, assessment and feedback, and doing research in their institution. Some instructors may see it as a valuable tool for generating creative content and aiding student learning. In contrast, others may have concerns about its potential to replace human creativity or biases in generated materials. Lecturers also view AI as a technology to achieve accessibility and equity after overcoming the challenges. Findings revealed that some measurements should be taken about the facilitating conditions and the perceived risks of using AI.

Topics & Concepts

CreativityExpectancy theoryThematic analysisPerceptionPsychologyHigher educationUnified theory of acceptance and use of technologyMathematics educationComputer scienceQualitative researchKnowledge managementSocial psychologySociologyLawSocial sciencePolitical scienceNeuroscienceAI in Service InteractionsTechnology Adoption and User BehaviourOrganizational and Employee Performance
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