Search Results (26)

Adaptive learning tailors learning to the specific needs and preferences of the learner. Although studies focusing on adaptive learning systems became popular decades ago, there is still a need for empirical evidence on the usability of adaptive learning in various educational environments. This study uses LMS log data to elucidate an adaptive course design explicitly developed for formal educational environments in higher education institutions. The framework utilizes learning analytics and machine learning techniques. Based on learners’ online engagement and tutors’ assessment of course activities, adaptive learning paths are presented to learners. To determine whether our system can increase learner engagement and prevent failures, learner success and engagement are measured during the learning process. The results show that the proposed adaptive course framework can increase course engagement and success. However, this potential depends on several factors, such as course organization, feedback, time constraints for activities, and the use of incentives. Full article

This qualitative study investigates how critical thinking is cultivated in postgraduate distance learning, focusing on two time points, 2016 and 2025, in the context of the Greek higher education system. It draws on semi-structured interviews with 30 participants (15 tutors and 15 students or graduates) from two online postgraduate programmes: Education Sciences and Education and Technologies in Distance Teaching and Learning Systems. Thematic analysis was used to explore participants’ perceptions of critical thinking development. The two-phase comparison captures how understandings and practices have evolved, particularly in light of the emergence of generative AI between 2016 and 2025. In Phase B, this research specifically examines AI’s potential role in supporting critical thinking and the pedagogical adaptations required by tutors. Nine key themes were identified. One of the most pressing concerns raised was that educators are perceived as largely ineffective in fostering critical thinking through online teaching. This study contributes empirical insight and practical recommendations to improve critical thinking cultivation in digital learning environments, especially in the age of AI. Full article

As large language models (LLMs) continue to evolve, their capacity to replace humans as their surrogates is also improving. As increasing numbers of intelligent tutoring systems (ITSs) are embracing the integration of LLMs for digital tutoring, questions are arising as to how effective they are and if their hallucinatory behaviors diminish their perceived advantages. One critical question that is seldom asked if the availability, plurality, and relative weaknesses in the reasoning process of LLMs are contributing to the much discussed digital divide and equity and fairness in online learning. In this paper, we present an experiment with database design theory assignments and demonstrate that while their capacity to reason logically is improving, LLMs are still prone to serious errors. We demonstrate that in online learning and in the absence of a human instructor, LLMs could introduce inequity in the form of “wrongful” tutoring that could be devastatingly harmful for learners, which we call ignorant bias, in increasingly popular digital learning. We also show that significant challenges remain for STEM subjects, especially for subjects for which sound and free online tutoring systems exist. Based on the set of use cases, we formulate a possible direction for an effective ITS for online database learning classes of the future. Full article

Given the advancements in artificial intelligence and extended reality technologies, this study aims to examine the integration of intelligent tutoring systems into augmented reality and virtual reality environments through a systematic literature review. Following the PRISMA framework, 32 related theoretical, showcase, and case studies published during the period of 2015–2024 are examined. Based on the results, this combination of technologies emerged as an effective educational means that can support both students and teachers, promote lifelong learning, and support face-to-face, blended, and online learning across educational levels and in the workplace. These systems offered immersive, realistic, and interactive learning environments and personalized learning experiences. Additionally, they could identify, monitor, and analyze students’ characteristics, performance, preferences, and motivational, cognitive, and psychological states. These systems could also adapt the learning content, resources, activities, and assessment according to students’ needs and make suitable recommendations. Their ability to offer tailored and real-time feedback, guidance, analytics, and evaluation was highlighted. Additionally, it was revealed that these systems offer meaningful learning experiences and enhance cognitive, affective, psychomotor, and embodied learning through self-directed learning, collaborative learning, personalized learning, and experiential learning approaches. Regarding learning benefits, students who learnt using this combination demonstrated increased engagement, motivation, confidence, immersion, and enjoyment. The students also reported better learning outcomes and academic performance, enhanced knowledge and skills, and improved information understanding and recall. This study also presents the main topics and areas examined, goes over the existing challenges, and suggests future research directions. Finally, the study emphasizes the importance of capitalizing on both human intelligence and machine intelligence to support students, meet their needs, and provide them with quality education and lifelong learning opportunities. Full article

Most of today’s educators are in no shortage of digital and online learning technologies available at their fingertips, ranging from Learning Management Systems such as Canvas, Blackboard, or Moodle, online meeting tools, online homework, and tutoring systems, exam proctoring platforms, computer simulations, and even virtual reality/augmented reality technologies. Furthermore, with the rapid development and wide availability of generative artificial intelligence (GenAI) services such as ChatGPT, we are just at the beginning of harnessing their potential to transform higher education. Yet, facing the large number of available options provided by cutting-edge technology, an imminent question on the mind of most educators is the following: how should I choose the technologies and integrate them into my teaching process so that they would best support student learning? We contemplate over these types of important and timely questions and share our reflections on evidence-based approaches to harnessing digital learning tools using a Self-regulated Engaged Learning Framework we have employed in our research in physics education that can be valuable for educators in other disciplines. Full article

At present, the integration of technology into education has generated a significant change in the way students access knowledge and develop skills. The availability of digital tools and online platforms has democratised access to information, allowing students to learn from anywhere and at any time. This article focuses on how the combination of artificial intelligence digital tools, such as ChatGPT, with one-to-one tutoring affects the development of soft skills in higher education students. A total of 182 university students participated in the study, divided into two groups. One group was required to construct an academic topic autonomously using only ChatGPT. The other group used the ChatGPT tool in conjunction with personal tutoring, with the teacher present to expand knowledge and enrich learning. The findings suggest that a combination of technology and meaningful human interactions is necessary to optimise the educational experience. While digital tools can be beneficial in accessing knowledge and developing skills, it is essential to acknowledge the value of individual connections with teachers in fostering authentic and deep learning. Furthermore, the study considers the potential necessity to modify and refocus both teaching participation and the student assessment system. This would entail a shift away from an emphasis on the memorisation of theoretical knowledge and towards the training and development of soft skills, competences, values and social implications. Full article

In forecasting research, the focus has largely been on decision support systems for enhancing performance, with fewer studies in learning support systems. As a remedy, Intelligent Tutoring Systems (ITSs) offer an innovative solution in that they provide one-on-one online computer-based learning support affording student modelling, adaptive pedagogical response, and performance tracking. This study provides a detailed description of the design and development of the first Forecasting Intelligent Tutoring System, aptly coined FITS, designed to assist students in developing an understanding of time series forecasting using classical time series decomposition. The system’s impact on learning is assessed through a pilot evaluation study, and its usefulness in understanding how students learn is illustrated through the exploration and statistical analysis of a small sample of student models. Practical reflections on the system’s development are also provided to better understand how such systems can facilitate and improve forecasting performance through training. Full article

The rapid changes in digital technology have had a substantial influence on education, resulting in the development of learning technologies (LTs) such as multimedia, computer-based training, intelligent tutoring systems, serious games, social media, and pedagogical agents. Serious games have demonstrated their effectiveness in several domains, while there is contradictory data on their efficiency in modifying behavior and their possible disadvantages. Serious games are games that are specifically created to fulfill a primary goal other than entertainment. The objective of our study is to evaluate the effectiveness of a serious game designed for the self-assessment of students concerning their knowledge of web technologies on students with an equivalent online quiz that uses the same collection of questions. The primary hypotheses we stated were that those utilizing the serious game would experience better results in terms of engagement, subjective experience, and learning compared to those using the online quiz. To examine these research questions, the IMI questionnaire, the total number of completed questions, and post-test grades were utilized to compare the two groups, which consisted of 34 undergraduate students. Our findings indicate that the serious game users did not have a better experience or better learning outcomes, but that they engaged more, answering significantly more questions. Future steps include finding more participants and extending the experimental period. Full article

Background: ultrasound diagnostics have a broad spectrum of applications, including among diseases of the musculoskeletal system. Accordingly, it is important for the users to have a well-founded and up-to-date education in this dynamic examination method. The right balance between online and in-class teaching still needs to be explored in this context. Certifying institutions are currently testing digitally transformed teaching concepts to provide more evidence. Methods: this study compared two musculoskeletal ultrasound blended learning models. Model A was more traditional, with a focus on in-person teaching, while Model B was more digitally oriented with compulsory webinar. Both used e-learning for preparation. Participants completed evaluations using a seven-point Likert scale, later converted to a 0–1 scale. Digital teaching media (e-learning) were used for preparation in both courses. Results: the analysis included n = 41 evaluations for Model A and n = 30 for Model B. Model B received a better overall assessment (median: 0.73 vs. 0.69, p = 0.05). Model B also excelled in “course preparation” (p = 0.02), “webinar quality” (p = 0.04), and “course concept” (p = 0.04). The “gain of competence” (p = 0.82), “learning materials” (p = 0.30), and “tutor quality” (p = 0.28) showed no significant differences. Conclusion: participants favorably assessed blended learning in ultrasound teaching. Certifying institutions should consider accrediting models that combine digital methods (e.g., internet lectures/webinars) and materials (e.g., e-learning) with hands-on ultrasound training. Further research is needed to validate these subjective findings for a stronger evidential basis. Full article

College students face significant challenges during large-scale disease outbreaks that potentially compromise their basic needs, vaccine confidence, and academic success. Using a cross-sectional design and convenience sampling, we examined the impact of COVID-19 among college students (N = 828). The survey was administered using the Qualtrics survey platform to collect data on multiple demographic and health behaviors of students in the summer semester (2021). Our study demonstrated that the most common financial shock experienced by the study participants was job loss, with less remarkable changes in food and housing insecurities. Academically, students had the most difficulty learning online compared to other modalities (face-to-face, Hyflex, etc.) and struggled with staying motivated. They also struggled with group work and finding appropriate learning spaces. However, many did not use university support systems such as career and tutoring services. Exploring the COVID-19 vaccination attitudes, we found that only age, ethnicity, classification, and health insurance status were associated with getting vaccinated (p < 0.05). When the learning environment was assessed for various modalities, only college attendance was significantly associated (p < 0.05) with the accessible platforms (online, Hyflex, face-to-face, and others); however, nearly 40% of students reported difficulty learning on an online learning platform compared other categories that had much lower proportions. Our findings underscore an immediate need for universities to take measures to improve their preparedness and response strategies to mitigate the negative effects of future large-scale public health emergencies among students. Full article

Student-athletes frequently struggle to strike a balance between their academic and athletic responsibilities. Various factors, such as age and competitive level, contribute to differences in their academic motivation and identity, showcasing the multifaceted needs they possess. While self-determination theory (SDT) has been proven effective for explaining student-athletes academic needs, its integration into learning design for this group remains limited. The developing AI technology, especially the Intelligent Tutoring System (ITS), offers the potential for creating personalized learning environments that can cater to the varying levels of motivation among student-athletes within the framework of SDT. Therefore, our paper explored how to build an SDT-based ITS for student-athletes to enhance their academic engagement and motivation. A two-stage experiment was conducted for: (a) identifying academic challenges faced by student-athletes in an online ITS; (b) evaluating the effectiveness of an SDT-based ITS design; and (c) exploring how autonomy, competence, and relatedness design affect their motivation. Results revealed that student-athletes face three challenges in learning in ITS: inflexible technology, identity missing, and mismatched learning difficulty. However, a significant improvement in academic engagement and motivation was shown when student-athletes faced an SDT-based ITS. In the meantime, the athletic motivation, which leads them to higher athletic performance, remains preserved and unaffected, showing a favorable outcome for student-athletes. This paper can provide practical implications for building a more inclusive and diverse learning environment for student-athletes. Full article

Currently, e-learning has revolutionized the way students learn by offering access to quality education in a model that does not depend on a specific space and time. However, due to the e-learning method where no tutor can directly control the group of students, they can be distracted for various reasons, which greatly affects their learning capacity. Several scientific works try to improve the quality of online education, but a holistic approach is necessary to address this problem. Identifying students’ attention spans is important in understanding how students process and retain information. Attention is a critical cognitive process that affects a student’s ability to learn. Therefore, it is important to use a variety of techniques and tools to assess student attention, such as standardized tests, behavioral observation, and assessment of academic achievement. This work proposes a system that uses devices such as cameras to monitor the attention level of students in real time during online classes. The results are used with feedback as a heuristic value to analyze the performance of the students, as well as the teaching standards of the teachers. Full article

This small-scale study explores the attitudes of fifty initial teacher education (ITE) subject methods tutors towards the use of virtual reality (VR) in education and considers whether VR could be a catalyst for reviewing the partnership model within ITE programmes. In addition, this study offers a novel solution to ITE tutors’ challenges when managing their own technological and pedagogical development alongside preparing student teachers for technology-enhanced learning (TEL). Building on previous research on ITE tutors’ use of TEL across the island of Ireland, this paper discusses the synergy between the cognitive apprenticeship model and reverse mentoring that upends the classic co-operating teacher/student teacher hierarchy and positions all partners in ITE programmes as learning leaders at key points in the partnership process. An online survey comprising 51 items was administered to a purposive sample of 50 ITE tutors from four ITE providers, two in Ireland and two in Northern Ireland (NI), who were selected due to their developing interest in the use of virtual reality in teacher education. Data analysis using SPSS combined with thematic analysis of open-ended responses revealed that although the majority of ITE subject methods tutors conveyed open-minded and willing attitudes to embrace VR in the future, they identified a number of systemic issues that need to be addressed first. These include the disconnect between innovative pedagogical practices presented in university-based modules and the stark reality of technological deficits in some classrooms; the pedagogical and resource-based ‘readiness’ of ITE tutors to embed VR in their subject-specific teaching; and the need for curriculum-focused, VR resources for school-based use. As a result of this study, an incremental, cyclical approach to growing the body of knowledge around VR pedagogy is proposed in conjunction with new forms of collaboration between the partners in ITE. Full article

This paper focuses on the use of mobile technology to assist teaching and learning in distance education. It aims to investigate teaching behaviour in mobile pedagogy and examine the impact of technology on current education. A case study was conducted through semi-structured interviews with a cohort of 30 Chinese lecturers who taught English through online tutoring. Thematic analysis was used to analyse the interview data and the assessment was based on teacher perceptions of mobile pedagogy. The impact of technology on the current educational environment is discussed through an analysis of mobile pedagogy and teacher perceptions. The findings show that mobile pedagogy is highly regional in practice and nature and features in-country software applications and social communication tools. Despite the attributes of connectivity and flexibility, mobile pedagogy only disrupted traditional teaching methods, leading to minimal changes to the education system. This study provides recommendations for the sustainable development of mobile pedagogy for future education systems in the digital age. Full article

The use of artificial intelligence and machine learning techniques across all disciplines has exploded in the past few years, with the ever-growing size of data and the changing needs of higher education, such as digital education. Similarly, online educational information systems have a huge amount of data related to students in digital education. This educational data can be used with artificial intelligence and machine learning techniques to improve digital education. This study makes two main contributions. First, the study follows a repeatable and objective process of exploring the literature. Second, the study outlines and explains the literature’s themes related to the use of AI-based algorithms in digital education. The study findings present six themes related to the use of machines in digital education. The synthesized evidence in this study suggests that machine learning and deep learning algorithms are used in several themes of digital learning. These themes include using intelligent tutors, dropout predictions, performance predictions, adaptive and predictive learning and learning styles, analytics and group-based learning, and automation. artificial neural network and support vector machine algorithms appear to be utilized among all the identified themes, followed by random forest, decision tree, naive Bayes, and logistic regression algorithms. Full article