Competency-based education in social work (CSWE, 2022) demands active learning methods that demonstrate professional competencies and practice behaviors. Role-plays and simulations are methods that link learning in the classroom with practice. This article explores role-play and simulation variants: basic role-play, real play, student-scripted…

The purpose of this study was to investigate student perceptions and acceptance of a rule-based educational chatbot in higher education, employing the TAM (Technology Acceptance Model) framework. The researchers developed a rule-based chatbot for this purpose and examined the students' technology acceptance using qualitative research methods.…

Random forests are a nonparametric machine learning method, which is currently gaining popularity in the behavioral sciences. Despite random forests' potential advantages over more conventional statistical methods, a remaining question is how reliably informative predictor variables can be identified by means of random forests. The present study…

In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…

Generative Artificial Intelligence (GAI) holds promise for enhancing the educational experience by providing personalized feedback and interactive simulations. While its integration into classrooms would improve education, concerns about how students may use AI in the class has prompted research on the perceptions related to the intention to…

The introduction of large language models (LLMs) may change future pedagogical practices. Current research mainly focuses on the use of LLMs to tutor students, while the exploration of LLMs' potential to assist teachers is limited. Taking high school mathematics as an example, we propose a method that utilizes LLMs to enhance the quality of…

In this study, we aimed to examine graduate students' experience when working with peers to complete a learning task focused on conducting a program evaluation in a qualitative research course. A generative artificial intelligence (GenAI)-powered platform was incorporated to support an experiential learning activity designed by the…

Background: For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require each document first be manually coded for constructs of interest by trained human raters. These hand-coded scores are then used as a measured outcome for an impact analysis, with the average scores of the treatment group…

Digital technology is profoundly transforming various aspects of life, thus highlighting the need to enhance digital literacy on a national scale. In primary and secondary schools, artificial intelligence (AI) education plays a pivotal role in fostering digital literacy. To comprehensively investigate the variables influencing AI education in…

Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…

Learning engagement is an essential indication to define students' learning pacification in the class, and its automated identification technique is the foundation for exploring how to effectively explain the motive of learning impact modifications and making intelligent teaching choices. Current research have demonstrated that there is a direct…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

Working collaboratively in groups can positively impact performance and student engagement. Intelligent social agents can provide a source of personalized support for students, and their benefits likely extend to collaborative settings, but it is difficult to determine how these agents should interact with students. Reinforcement learning (RL)…

Contribution: A novel proactive and collaborative learning paradigm was proposed to engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary artificial intelligence (AI)-cybersecurity knowledge. Specifically, the proposed learning paradigm contains: 1) an immersive learning environment to…

Experiential learning plays an important role in teaching business law. This paper builds upon prior research regarding the use of experiential learning activities to teach contract law, by adding the use of generative artificial intelligence to a contract simulation activity. As part of a multi-week, in-class simulation, students used generative…