Exploring college students’ awareness and use of AI-enhanced flipped classroom models: Impacts on learning outcomes and skills development

Exploring college students’ awareness and use of AI-enhanced flipped classroom models: Impacts on learning outcomes and skills development
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A B S T R A C T

This study examines college students’ awareness of and use of artificial intelligence (AI) in flipped classroom activities that involve Mathematics in the Modern World. The flipped classroom promotes self-paced learning and collaboration by having students work on learning materials outside of class and participate in interactive exercises in class. AI tools, increasingly prevalent in education, offer personalized support for college students through tutoring systems, problem-solving platforms, and chatbots, complementing the flipped classroom model. Furthermore, this assesses college students’ awareness of AI regarding the flipped classroom model, emphasizing advantages like participation, engagement, problem-solving skills, study habits, and academic achievement. It also looks into the AI tools that college students use to improve their education. The methodology involves 65 volunteer college students from the University of Makati who participate in a descriptive approach using a Likert scale questionnaire to assess student awareness across multiple aspects. Preliminary results show that college students are highly aware of the flipped classroom model, recognizing its impact on participation, problem-solving, and time management. They also demonstrate a strong awareness of AI’s potential to provide personalized feedback and improve academic performance, although practical usage of AI tools like chatbots and tutoring systems remains moderate. Although students understand the function AI plays in flipped classrooms, more integration and training are required to realize the potential advantages of these tools fully. The study highlights how crucial it is to promote digital literacy and individualized learning through AI-driven educational advancements.

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Artificial intelligence in recruitment: Assessing flipside

Hema Mirji
Bharati Vidyapeeth (Deemed to be University), Pune, India
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A B S T R A C T
Artificial Intelligence is used for various business processes including hiring employees. The purpose of this article is to assess the flip-side of Artificial Intelligence applied in recruitment software. Its insufficiency of delivering the expected results in terms of the right match for the hiring, difficulty in language processing. The paper reviews the literature available to understand the principles of Socio-technical systems design requirements and on Artificial Intelligence’s usage in the recruitment process. The research is qualitative, has followed the phenomenology approach, and uses the interview technique for understanding the opinions of the users. The results reveal that, though AI in recruitment provides ease in searching the candidate’s barriers in language and recognition, low turn-in ratio, incorrect recommendations due to Data inadequacy, skepticism among HR professionals due to lack of human intelligence, need for budgets for acquiring and training are issues. It is proposed to incorporate the guidelines of Socio-Technical System Design and Human-machine teaming for designing the Artificial Intelligence tools. Further studies could be conducted to understand the limitations of the frameworks available for designing such tools.

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