Awareness

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

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

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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Factors affecting the readiness of digital transformation adopters: A case study in Vietnam

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Vinh T. Nguyen, Hue T. Lai, Quynh V. Ha
Corresponding email: [email protected]

A B S T R A C T

In the age of industry 4.0, digital transformation is becoming an increasingly popular term. Prior studies concentrated on advantages and research agenda, but little attempts were made to comprehend and evaluate the postulated conceptual model. Thus, the aim of this research was to understand the latent variables that affected the readiness of digital transformation adopters as well as the importance level between those dimensions. The 12-question survey was designed using Google Form and sent to 97 students of the digital transformation training class. Exploratory factor analysis and multivariate regression were utilized to analyze the obtained survey data. The findings showed that there were 4 main factors affecting the readiness of digital transformation including awareness, facilitating conditions, knowledge and behavioral intention. The total variance extracted by these 4 factors explained 61% of the data variation of 12 observed variables. The results of multivariable regression analysis demonstrated that all extracted factors had an important influence on the readiness of students to transform digitally, in which “behavioral intention” played the most important role. The research results help policy makers and educators have a better overview, thereby making strategies and adjusting plans according to the priority level around the above 4 factors. It also serves as a basis for other in-depth studies, and as a reference for interested digital transformation readers.

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Knowledge and awareness on cardiovascular diseases among the Iraqi population

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Taqi Mohammed Jwad Taher, Shaymaa Abdul Lateef Alfadhul, Ammar Shimal Shwekh, Firas Turki Rashed Sarray   
Wasit University, Wasit, Iraq
University of Kufa, Kufa, Iraq
Al-Zahraa Teaching Hospital, Wasit Health Directorate, Wasit, Iraq
Corresponding email: [email protected]

A B S T R A C T
This community-based, cross-sectional study was conducted to assess the knowledge on cardiovascular diseases among the Iraqi population. The sample was convenient and included all populations aged between 18-80 years old. Data were collected during the period from 1st to 15th of August using a structured questionnaire which was distributed to the participants via Facebook, Telegram, and WhatsApp. All data were entered into the computer software program SPSS version 26 for statistical analysis. Association between variables was assessed by Chi-square test and independent-sample t-test accordingly. The 974 respondents were with a mean age of 37 years. Females represented 71% of them. Around 18% had an overall poor knowledge, whereas 49% and 33 % had moderate and good knowledge respectively. More than two-thirds of respondents (69.8%) identified coronary heart disease as a type of CVDs. Chest pain or discomfort was distinguished as a symptom of heart attack by 84%. Sudden confusion or disturbed consciousness was recognized by 73% as warning symptoms of stroke, whereas severe headache of unknown cause was recognized by only 48%. Most of the participants (91.2%) knew that obesity is a risk factor for this disease, but only 55% identified diabetes as its cause. Overall knowledge related to CVDs is acceptable. Unsatisfactory awareness about types and warning symptoms of CVDs although of good awareness about risk factors. Important determinants of knowledge on CVDs are gender, educational level, residence, monthly income, body mass index, family history of CVDs, perception of lifestyle, and personal history of diabetes or hypertension. The researchers recommend further studies including different educational and socioeconomic classes.

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