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The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.

Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.

The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.

The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.

E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.

A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

The principal aim of this research is to acquire a deeper understanding of the opinion held by the training and development (T&D) professionals, regarding the use of artificial intelligence (AI) technology in the area of T&D. Particularly in response to the evolving needs of learners, the research aims to ascertain T&D professionals' perspective on the efficiency of AI in fostering T&D, while understanding the constraints and limitations associated with this technology.

The study is based on qualitative data. With the help of semi-structured interviews, qualitative data has been collected from 21 T&D professionals. Experts working with multinational corporations (MNCs) are selected as a study sample using a convenient sampling technique. Qualitative data were analysed using thematic analysis. Conclusions were drawn based on the results of thematic analysis.

The findings of the study have revealed a notable and rapid evolution in the requirements of learners, particularly during and post-COVID-19 period. AI-based technology has emerged as a significant contributor, offering learners distinct personalised experiences and enhanced convenience. However, the implementation of AI in training remains in its early stages and has not reached widespread adoption. The findings of the study also highlighted various challenges and limitations, while using AI-based technology for training. It has been found that AI complements rather than replaces the role of a physical trainer.

The originality of this study lies in the application of AI-based training for professional learners, from the perspective of the T&D practitioners working with MNCs in Maharashtra, India. Numerous studies that have recently been published, emphasise the areas in which AI technology can transform the T&D industry. Yet, there are currently very less studies that have attempted to understand the evolving needs of learners and support of AI-based training for the same, from the perspective of the T&D professionals working in Maharashtra, India.

The purpose of constructing the collage and stimulus instruments was to assess the learners’ attainment of the learning outcomes of the life skills learning programme. The collage is a compilation of pictures and concepts representing the different skills included in the life skills learning programme, and the pictures and concepts acted as the stimulus instruments. Subsequently, the collage and stimulus instruments were used in a first assessment directly after the learners had completed the life skills learning programme. The development of the data category classification enabled the researcher to evaluate and interpret the responses of the learners in the assessments and to ascertain to what extent the learning outcomes of the life skills learning programme were attained. It was found that the collage and stimulus instruments were effective in assessing the learners’ attainment of the learning outcomes of the life skills learning programme. However, it must be noted that the findings on the behavioural changes in the learners again highlighted the difficulties in assessing the affective domain in life skills.

Interactive activities are an important aspect of distributed learning situations, wherein online communities and learner motivational levels evolve and thrive. Through the thoughtful integration of interactive activities into the online learning process, learners and instructors gain considerable exposure to reciprocally favorable occurrences among learners, content, interface, instructor, community, and self. The thoughtful design and development of a distributed learning environment aids the use of interactive activities in moving beyond mere online interactions towards a more theoretically productive level of interactions. Within a theoretically productive level of interaction wherein the learners obtain information, develop conceptual frameworks through which the information is not only derived but becomes useful knowledge, develop higher‐level thinking skills, and continue to be internally motivated to continue with the course, the learners conceptualize a learning community which can be sorely lacking within distributed learning situations that do not integrate appropriate interactive activities.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether social media affordances and media richness as environmental stimuli to learners’ involvement elicited by massive open online courses (MOOCs) can affect their learning persistence in MOOCs and, in turn, their learning outcomes in MOOCs. This study further examines whether demographic variables can moderate the relationship between learners’ learning persistence in MOOCs and their learning outcomes.

Sample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 396 usable questionnaires were analyzed using structural equation modeling.

This study proved that learners’ perceived social media affordances and media richness in MOOCs positively influenced their cognitive involvement and affective involvement elicited by MOOCs, which concurrently expounded their learning persistence in MOOCs and, in turn, uplifted their learning outcomes in MOOCs. The results support all proposed hypotheses and the research model, respectively, explains 70.5% and 61.8% of the variance in learners’ learning persistence in MOOCs and learning outcomes. Besides, this study showed that learners’ usage experience moderated the relationship between learners’ learning persistence in MOOCs and their learning outcomes.

This study uses the S-O-R model as a theoretical groundwork to construct learners’ learning outcomes in MOOCs as a series of the psychological process, which is affected by social media affordances and media richness. Noteworthily, while the S-O-R model has been extensively used in previous literature, little research uses the S-O-R model to explain the media antecedents of learners’ learning persistence and learning outcomes in MOOCs. Hence, this study enriches the research for understanding how learners value their learning gains via using media features to support them in MOOCs.

Hybrid learning has become a reality due to the onslaught of the COVID-19 pandemic. Students world over had to switch to this new learning format. This study aims to analyze the impact of innovation attributes of the Unified Theory of Acceptance and User Technology (UTAUT2) model and community of inquiry (COI) framework on the hybrid learning experience and the continued intention for it.

Using a cross-sectional research design, the study has adapted a scale from past studies and collected data using purposive sampling from the student community. The research has used the structural equation modeling technique using SMART-PLS to study the hypothesized relationships.

The study’s findings are that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, teaching presence, cognitive presence and social presence influence hybrid learning experience and continued intention. Further hybrid learning experience mediates the continued intention.

This study has several academic and practical implications for improving the hybrid learning experience. Various stakeholders can get insights on improving the user’s desire to pursue learning in a hybrid environment.

Hybrid learner experience is an upcoming area of research and yet unexplored in India as well as in other countries. A new hybrid experience model was developed by extending the UTAUT2 to include the COI framework and learner experience frameworks.

This paper presents a framework that training professionals may utilize to develop training to align learner preferences with organizational objectives.

The authors of this paper present a framework they have used throughout the United States to prepare and develop training aligned with organizational objectives and learners' preferences in the workplace.

This paper highlights the importance of understanding organizational objectives and learner preferences when designing training and provides a framework to assist trainers. Using this framework, the authors have found that they can quickly adjust training sessions to a target audience with a broad range of personalities and preferences with good results.

This framework provides training practitioners with a step-by-step guide for quickly considering the alignment of organizational objectives to learner characteristics to enhance training design.

The purpose of this study is to propose a research model based on the stimulus–organism–response (S–O–R) model to examine whether network externality, personalization and sociability as environmental feature antecedents to learners’ learning engagement (LE) can influence their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 371 usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that learners’ perceived network externality, personalization and sociability in MOOCs positively affected their cognitive LE, psychological LE and social LE elicited by MOOCs, which jointly led to their LP in MOOCs. The results support all proposed hypotheses, and the research model accounts for 76.2% of the variance in learners’ LP in MOOCs.

This study uses the S–O–R model as a theoretical base to construct learners’ LP in MOOCs as a series of the inner process, which is affected by network externality, personalization and sociability. It is worth noting that three psychological constructs including cognitive LE, psychological LE and social LE are used to represent learners’ organismic states of MOOCs usage. To date, hedonic/utilitarian concepts are more often adopted as organisms in previous studies using the S–O–R model, and psychological constructs have received lesser attention. Hence, this study’ contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners’ LP in MOOCs is well documented.

The existing traditional recommendations based on content-based filtering (CBF), collaborative filtering (CF) and hybrid approaches are inadequate for recommending practice challenges in programming online judge (POJ). These systems only consider the preferences of the target users or similar users to recommend items. In the learning environment, recommender systems should consider the learning path, knowledge level and ability of the learner. Another major problem in POJ is the learners don't give ratings to practice challenges like e-commerce and video streaming portals. This purpose of the proposed approach is to overcome the abovementioned shortcomings.

To achieve the context-aware practice challenge recommendation, the data preparation techniques including implicit rating extraction, data preprocessing to remove outliers, sequence-based learner clustering and utility sequence pattern mining approaches are used in the proposed approach. The approach ensures that the recommender system considers the knowledge level, learning path and learning goals of the learner to recommend practice challenges.

Experiments on practice challenge recommendations conducted using real-world POJ dataset show that the proposed system outperforms other traditional approaches. The experiment also demonstrates that the proposed system is recommending challenges based on the learner's current context. The implicit rating extracted using the proposed approach works accurately in the recommender system.

The proposed system contains the following novel approaches to address the lack of rating and context-aware recommendations. The mathematical model was used to extract ratings from learner submissions. The statistical approach was used in data preprocessing. The sequence similarity-based learner clustering was used in transition matrix. Utilizing the rating as a utility in the USPAN algorithm provides useful insights into learner–challenge relationships.

This paper evaluated the effectiveness of blended learning of business courses in higher learning institutions (HEIs) in developing economies.

A survey, involving 215 learners, was used to collect data. A stratified sampling technique was used in this study. The data were analyzed using the PROCESS macro in SPSS.

In the blended learning approach, student attitudes, social presence, IT infrastructure and flexible learning are all favorable predictors of learner satisfaction. The impact of blended learning on learner satisfaction is further mediated by IT infrastructure, social presence and learner attitude.

HEIs need to invest in planning and resource mobilization in order to realize several benefits derived from the use of blended learning. For optimal learning outcomes, this should be combined with training on IT infrastructure usage for both facilitators and learners. In order to assist learners in developing competencies through consistent use, institutions should also invest in tailored blended learning technologies. In addition, emphasis should be placed on training all actors in order to better manage change.

This paper presents and ranks several dimensions for blended learning success in low-budget universities. In addition, the study contributes to the understanding of intervening variables necessary for enhancing the potential of pedagogy in maximizing learner satisfaction.