As the popularity and accessibility of artificial intelligence (AI) in learning continue to rise, online education has increasingly incorporated AI. It is imperative to investigate how AI in the scholarly community supports the learning of autonomous students. This scoping review investigated articles that employed AI in discussion forums. The objective of this study is to develop a summary that denotes the effective integration of AI in discussion forums, thereby characterizing the overall learning experience. In accordance with the search, appraisal, synthesis, and analysis (SALSA) framework, the preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram was employed to design the article screening and selection process. Scopus was utilized for the literature search, resulting in the identification of twelve articles that met the predetermined inclusion and exclusion criteria. The extracted articles covered the following six applications: intelligent tutoring systems, AI-assisted apps, chatbots, automatic formative assessment, AI teaching assistants, and AI-assisted lifelong learning assistants. Three types of man-machine partnerships related to the activities are discussed: student-AI partnerships, student-AI-student partnerships, and student-AI-teacher partnerships, the latter being the most commonly observed. The generated content was frequently processed through teacher adjustments and checks. Components of community of inquiry theory were adapted as indicators. Cognitive presence was observed to be more predominant than social presence, with a particular emphasis on individual learning achievements. Three distinct perspectives regarding the role of AI in learning were identified. The first perspective posited that AI functioned as a virtual teacher, supplementing the teaching functions of human teachers and delivering information to students. In the second perspective, AI facilitated students in collecting information by enabling interactions with messages or peers. In the third perspective, the significance of the automatic evaluation function, which assessed learning activities and provided feedback to enhance the system while simultaneously implementing immediate changes in the learning process, was acknowledged. Regarding the role of communication, teachers clearly intended for students to acquire knowledge through it. Despite the focus on assisting individual learners, each article encompassed references from a wide range of fields and exhibited substantial diversity overall. Consequently, the domain of discussion forums with AI was depicted through the complex interplay between technology, pedagogy, and the learning environment. This context is known as entangled pedagogies, which emphasize understanding the interconnections among these elements and their reciprocal influences. In summary, AI was predominantly utilized in the form of chatbots and GenAI in discussion forums. Emerging AI roles included virtual teachers, peer/message matching, and automated evaluation. Aggregated information was presented in a manner that supported student learning. AI also served as a conduit between students and teachers.

Gamification has emerged as a promising strategy to enhance student engagement and learning outcomes in computer science education. This study uses Wenger's Value Creation Framework to evaluate and design the gamification elements in the Answers platform, a Professional Learning Network (PLN) developed at TU Delft. Using a mixed-methods approach with 372 participants, this research examines the platform's impact on learning, motivation, and social interaction. Findings indicate that the platform significantly enhances academic engagement and applied value, as students actively use it for knowledge acquisition and problem-solving. However, social connectivity remains limited, as reflected in lower scores for relatedness and potential value. Qualitative insights reveal that students primarily engage with the platform for academic support rather than networking or peer collaboration. This study contributes to e-learning practice by offering design recommendations to integrate collaborative learning elements better and foster social interaction within gamified learning environments. Additionally, it advances theoretical discussions on gamified PLNs by illustrating how Wenger's framework can be operationalized to assess value creation in digital learning networks. The findings highlight the need for a more holistic approach to gamification that extends beyond point-based rewards to include community-driven engagement mechanisms. By addressing these gaps, this research provides actionable insights for educators, platform designers, and policymakers, supporting the development of more effective gamified learning environments that balance motivation, collaboration, and engagement in online education.

This study delves into the adoption of chatbot technology in higher education, with a focus on Indonesian online learning environments. Recognizing the potential of AI-driven tools to address academic support gaps, particularly in developing regions, the research explores how performance expectancy, effort expectancy, and facilitating conditions influence students' behavioral intentions and subsequent adoption of chatbots for academic use. The study employs Structural Equation Modeling (SEM) to analyze survey data from a diverse sample of university students, enabling a nuanced understanding of the complex relationships among these factors. The findings reveal that performance expectancy—the belief that chatbots will enhance academic performance and facilitating conditions, such as internet access and institutional support, play significant roles in motivating students to adopt chatbots. However, effort expectancy, or the perceived ease of use, does not directly drive adoption intentions. This suggests that students prioritize practical benefits over user-friendliness, an insight valuable for universities aiming to implement effective chatbot systems. Moreover, the results align with the Socio-Technical Interaction Network (STIN) model, which emphasizes the need for a cohesive social and technical framework to foster technological acceptance. The STIN model’s perspective underscores that students' engagement with chatbots is not just a matter of usability but also of how well the technology is supported by the broader educational infrastructure. This study offers actionable insights for Indonesian universities and other institutions in similar contexts, proposing that enhancing campus resources, like reliable internet access and technical support, can drive chatbot adoption. By focusing on performance-based benefits and strengthening the socio-technical environment, universities can effectively integrate AI-based learning tools, addressing both technical and socio-cultural barriers. Such initiatives support students’ learning experiences and foster an adaptive academic ecosystem where AI tools serve as essential assets in overcoming resource limitations. Thus, the study contributes a practical roadmap for advancing e-learning in resource-constrained settings through strategic support of AI technology adoption.

This study investigates influential aspects of students' acceptance of online learning: students' readiness, peer support, and instructional support. Readiness, driven by motivation, technical skills, and self-management, affects online learning participation. This readiness is made up of self-learning and communication abilities in online environments, which influence acceptance and satisfaction. Peer support inspires collaboration and enhances learning gains. It reduces loneliness, boosts motivation, and facilitates teamwork, while instructional support aids learning through organized interaction and feedback. Instructional support (e.g., immediate feedback and well-structured instruction) also improves engagement and perceived accomplishment in online education. The study employed a systematic sampling plan, using 308 students at an American university pursuing online or blended courses. Confirmatory factor analysis was used to validate the measurement model, confirming construct validity and reliability. Structural equation modeling confirmed the tested hypotheses and relationships among the variables. Students who perceive online learning as useful and convenient are more inclined to engage with the learning management system, which aligns with the technology acceptance model. Psychological, technological, and behavioral readiness play a primary role in determining whether self-efficacious and self-regulated learners will adapt. Peer support is important in offsetting the alienating effect of e-learning and facilitating engagement, motivation, and cognitive presence. Interpersonal behavior, such as peer mentoring and group discussion, increases social belonging, reduces anxiety, and develops academic resilience. Instructional support is critical to the acceptance of online learning. Timely scaffolding and immediate feedback increase students' engagement and motivation. Institutional investments in technical and non-technical resources enable active participation. The study's broader implications are multifaceted and require a holistic approach focusing on content delivery, actively preparing students, fostering social connections, and supporting them throughout their journey. Student readiness is not a static trait; rather, it can be intentionally developed over time. Administrators should take pre-emptive measures with course design and focused interventions, like student training that promotes independence and empowerment. Institutional-level policies promoting peer-to-peer cooperation will enable universities to raise the general acceptability of online learning, student involvement, and satisfaction. Instructional support must prioritize clarity and engagement to foster student acceptance of online learning. Institutions can significantly enhance the acceptance of online learning by employing academic and emotional support, integrating technology, and providing comprehensive learning support services. In addition, institutions must constantly build and maintain a solid technology and non-technology support system that includes e-advising, e-tutoring, and mental health counseling for online students. The study advances e-learning practices by reframing student readiness as a dynamic quality that organizations can cultivate with focused instruction and assistance. The results offer practical advice for creating welcoming, stimulating, and encouraging online environments that increase student acceptance of online learning.

This article investigates how the integration of ChatGPT could transform Peruvian universities by 2033. Twenty drivers were identified, including digital competencies, critical thinking, academic performance, and motivation. Using a foresight approach, possible future scenarios were generated. The methodology consists of four stages: (1) Exploration of the system to identify key drivers; (2) Validation of the information by applying the Delphi method in real time to confirm these drivers; (3) Construction of scenarios using Schwartz axes and structural analysis; and (4) Validation of scenarios using the Probability, Desirability and Governance (PDG) method. The analysis revealed that the most important and uncertain drivers are related to 'training in critical thinking, feedback through intelligent tutoring, and the development of technological infrastructure,' located in Schwartz's Quadrant III. These drivers are crucial to building four scenarios, including the target scenario dubbed "Overcoming Challenges with Innovation and Technology".

Computational thinking (CT) skills are increasingly important in education to prepare students for the challenges of the digital age. Augmented Reality (AR) and Virtual Reality (VR) have been introduced as immersive technologies that have the potential to enhance CT skills through more interactive learning experiences. However, there is still a gap in understanding the effectiveness of these technologies in supporting the development of CT, particularly in different levels of education and disciplines. Although several studies have highlighted the benefits of AR and VR in education, no systematic review integrates these findings to identify advantages, challenges, and opportunities for further implementation. Therefore, this study conducted a systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines by analyzing 25 empirical studies (AR=17, VR=8) obtained from the Scopus database (2008-2024). The analysis addresses four key research questions: (1) the current state of AR/VR in CT development, (2) their advantages, (3) implementation challenges, and (4) future research directions. The results show that AR is more widespread than VR at various levels of education, with dominance in higher education followed by secondary and primary schools. Computer science is the main field of application of AR and VR, while AR is also widely applied in mathematics to increase interest and problem-solving. A total of 11 studies reported significant impacts of these technologies on CT, with AR being superior in increasing student motivation and engagement, as well as aiding in problem-solving and debugging. In contrast, VR provides a more immersive learning experience by strengthening concept understanding, especially in programming and recursion. However, several obstacles in the application of AR and VR, such as hardware limitations, costs, and user skills, affect the effectiveness of these technologies in the learning environment. This study also identified potential future research, including the exploration of VR in primary and kindergarten education, the application of VR in non-computer science fields, and the efficient use of these technologies in supporting the CT process. This study provides more precise insights into the optimal ways of utilizing AR and VR in developing CT skills. It is a reference for educators, policymakers, and researchers in supporting CT learning.

As generative artificial intelligence tools like ChatGPT become increasingly integrated into educational environments, understanding their impact on critical thinking is crucial. Despite growing concerns about AI's potential to diminish students' independent reasoning, there is a lack of research tools specifically designed to evaluate students' perceptions of AI's cognitive capabilities. To address this gap, this study introduces the Perceived Critical Thinking Disposition of Generative Artificial Intelligence (PCTD-GAI) scale, aimed at measuring how students perceive generative AI’s (GAI) six critical thinking dispositions (reasoning, access to justice, search for evidence, search for truth, open-mindedness, and systematicity). While this study validates the scale using ChatGPT, the instrument is adaptable for evaluating other generative AI tools, supporting broader research in AI-driven learning environments, to assess not only how students engage with AI, but also how their reliance on AI may affect their cognitive development and self-regulated learning skills in digital education. To develop and validate the PCTD-GAI scale, the Marmara Critical Thinking Dispositions Scale (MCTDS) was adapted, ensuring relevance to AI assessment while maintaining conceptual robustness. A quantitative cross-sectional study was conducted with 931 university students from Portugal and Poland, employing exploratory and confirmatory factor analyses (EFA & CFA) to assess the scale’s validity and reliability. The results demonstrate that the PCTD-GAI effectively captures students’ perceptions of ChatGPT’s critical thinking dispositions across six key dimensions. Findings indicate moderately positive perceptions across both countries, with Portuguese students consistently rating ChatGPT marginally higher across domains and showing less response variability, suggesting greater consensus. Notably, perceptions were most neutral in the "truth-seeking" domain, while systematicity received the highest ratings, reflecting ChatGPT’s perceived systematic capabilities among students. These findings have significant implications for e-learning and AI-driven education. The PCTD-GAI scale enables educators to track students’ evolving AI literacy and develop targeted interventions that promote critical AI engagement rather than passive reliance on AI-generated content. Moreover, this research advances the field of e-learning by offering an empirical basis for integrating AI assessment into digital learning strategies, ensuring that AI serves as a cognitive tool rather than a substitute for independent reasoning. The validated PCTD-GAI scale provides a reliable, scalable method for assessing students’ perceptions of AI's cognitive capabilities, supporting evidence-based AI pedagogy, and guiding institutional policies on AI integration in education.

This study focuses on the role of innovation in educational technology, especially the use Virtual – Augmented Reality (VAR) at the junior high school level. The COVID-19 pandemic has widened the existing gap associated with technology and learning, calling for the need to provide interactive learning tools to develop students’ higher-order thinking skills (HOTS). This study aimed to design and determine the effectiveness of VAR learning tools on students’ HOTS skills. The research method used was Research and Development (R&D) using the Alessi and Trollip model, which includes three steps: planning, design, and development. The research population consisted of 242 junior high school students from Surakarta City, Indonesia, who were recruited through cluster sampling. Observations, interviews, and product feasibility questionnaires were used as instruments. The results showed that the students’ HOTS skills improved significantly with the use of VAR-integrated learning tools in science subjects. The learners’ mean scores on the post-test had a marked rise as opposed to the pre-test, signifying the effectiveness of the medium in greatly augmenting HOTS skills. This study suggests that VAR-based learning tools can be used as an effective means to overcome the digital divide and improve the quality of education by developing students' higher-order thinking skills, which are essential for 21st century learning.

Since the COVID-19 pandemic, the popularity of foreign language learning on mobile-assisted language learning (MALL) applications has increased. The MALL also implements a freemium (free access) and premium business model where customers must purchase the subscription package provided. This research aims to find out what factors influence the migration of users from the free version to the premium MALL version. This study uses a quantitative and qualitative approach. Quantitative data obtained through questionnaires filled out by 1,232 respondents and qualitative data obtained through interviews with thirty interviewees. The results of this study show that dissatisfaction in the push factor was found to be factors that significantly influenced the user's desire to switch to the premium version of the MALL, while perceived intrusiveness and perceived inefficiency did not have a significant positive effect on the user's desire to switch to the premium version of the MALL. The pull factor, perceived enjoyment, perceived usefulness, and trialability showed a significant positive influence, while the perceived learner value aspect did not show a significant positive influence. Finally, all aspects of the mooring factor, namely switching cost, social influence, and inertia show a significant influence on user intention to switch to the premium version of the MALL. However, switching cost showed positive influence on users’ switching intention, contrary to the predicted hypotheses. The results of this research are expected to be an input for MALL application developers to improve their services so that users switch to using the premium version of the MALL.

This study examines the usage of Zoom platform features and functions in managing EFL classes from the perspectives of students and their instructors. The study used a mixed-method approach. Quantitively, a questionnaire was distributed to undergraduate EFL students enrolled in advanced English courses (B2) in the first semester of the academic year 2023/2024 in a Palestinian university. The questionnaire was complemented by interviewing nine EFL instructors who have utilized the Zoom platform in their EFL classes. The quantitative data were subjected to statistical analysis whereas the interview data were analyzed thematically to obtain qualitative insights. The findings of the study revealed that Zoom features and functions significantly boost the online language learning experience in the EFL classes according to the students’ views. The students highly appreciate the features of recording, raising hands, screen-sharing, mute/unmute controls, file-sharing, and chat box while learning the English language. The results also indicate that both male and female students have similar views on the efficiency of Zoom features and functions. The analysis of the qualitative data reveals that EFL instructors largely utilize Zoom features and functions in their EFL classes and appreciate the benefits of these tools. Nevertheless, the results demonstrate that the instructors encounter some challenges primarily related to technical issues. The findings provide valuable views to the field of language learning and teaching through building on the experiences of undergraduate students and instructors with the context of EFL.