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Self-regulation is the level of learning where the learner becomes an active agent in their learning process in terms of activity and aspects of motivation and metacognition. The current paper mostly deals with the metacognitive aspect. The purpose of this study is to gain insight into self-regulation of learning in the context of modern technology in higher education. This study also aims to highlight the direction, tendencies and trends toward which self-regulation of learning is moving in relation to modern technologies.

The review study was compiled via searches in three databases: Scopus, Web of Science and ERIC. A filter was used to search for empirical studies solely in English, published over the past decade on the topics of self-regulation of learning and technology in higher education.

The findings clearly show a correlation between self-regulation of learning and modern technology, especially after a significant event such as the Covid-19 pandemic. However, in the wake of this change, the field of education has seen the emergence of methods and new platforms that can provide support for the development of self-regulated learning strategies.

The originality of the study lies in the fact that it focuses on the link between self-regulation of learning and modern technologies in higher education, including some predictions of the future direction of self-regulation of learning in this context.

As educational institutes began to address the challenges posed by COVID-19, e-learning came to the foreground as the best bet left. This study is in quest of revealing engineering student's perceptions of the available e-learning platforms, thus surfacing the underlying bottlenecks. Further, it aims at providing solutions that would help enhance the e-learning experience not only in pandemic times but also in the long run.

This holistic research begins with a comprehensive comparative study about the available e-learning platforms, followed by a primary data analysis through an online survey of 364 engineering students from various colleges and branches. The collected data was analyzed to detect bottlenecks in online learning and suggestions are given for solving some challenges.

On a five-point Likert scale, the available e-learning platforms garnered ratings ranging from 2.81 to 3.46. Google meet was the most preferred platform. However, with a net promoter score (NPS) of 30.36, Microsoft Teams emerged as the most satisfying platform. Technical shortcomings clubbed with psychological and biological factors were found to be taking a toll on e-learning.

This innovative research is based on the perceptions of engineering students hailing majorly from Indian cities, and hence, it may be having educational stream bias and geographical bias. The research could be further extended to cover rural areas and global trends in e-learning.

The research offers a thorough analysis of e-learning platforms, as seen through the lens of engineering students. Furthermore, the analysis does not constrain itself to the technicalities and thus proves to be an all-encompassing one, potent enough to surface critical issues marring the e-learning experience.

The study explores the perspectives of college students on the pedagogical shift as well as frequent transitions between online and offline learning modes during the COVID-19 pandemic in Kerala, the most literate state in India.

A descriptive cross-sectional study was conducted among 1,366 college students in Kerala during December 2021. A pre-tested questionnaire was sent using Google Forms to students of arts and science colleges. The authors analyzed quantitative data using descriptive statistics and qualitative data using thematic content analysis.

The reported advantages of online learning were increased technical skill, flexibility in study time, effectiveness in bridging the gap of the missed academic period and provision of attending more educational webinars. Students expressed concerns of increased workload, difficulty in concentration due to family circumstances, academic incompetency, uncleared doubts and addiction to mobile phones and social media during the online classes. The main advantages reported for switching to an offline learning mode were enhanced social interaction, effective learning, better concentration and reduced stress. The reported challenges of offline classes were fear of getting the disease, concern of maintaining social distancing and difficulty in wearing masks during the classes. The shift in offline to online learning and vice versa was perceived as a difficult process for the students as it took a considerable time for them to adjust to the switching process of learning.

Students' concerns regarding transition between different learning modes provide important information to educators to better understand and support the needs of students during the pandemic situations.

This paper aims to understand what drives people – their motivations, autonomous learning attitudes and learning interests – to volunteer as mentors for a program that helps families to ideate technological solutions to community problems.

A three-phase method was used to build volunteer mentor profiles; elicit topics of interest and establish relationships between those. The mentor profiles were based on self-assessments of motivation, attitude toward lifelong learning and self-regulated learning strategies. The topics of interest were elicited through content analysis of answers to reflection questions. Statistical methods were applied to analyze the relationship between the interests and the mentor profiles.

Bottom-up clustering led to the identification of three mentor groups (G1 “low”; G2 “high” and G3 “medium”) based on pre-survey data. While content analysis led to identifying topics of interest: communication skills; learning AI; mentoring; prototype development; problem-solving skills; working with families. Analyzing relationships between mentor profile and the topics of interest, the group G3 “medium,” with strong intrinsic motivation, showed significantly more interest in working with families. The group with the overall highest scores (G2 “high”) evidenced also substantial interest in learning about AI, but with high variability between members of the group.

The study established different types of learning interests of volunteer mentors and related them to the mentor profiles based on motivation, self-regulated learning strategies and attitudes toward lifelong learning. Such knowledge can help organizations shape the volunteering experience to provide more value to volunteers. Furthermore, the reflection questions can be used by volunteers as an instrument for reflection and by organizations to elicit the learning interests of volunteers.

Self-regulated learning (SRL) is crucial for successful learning and lifelong learning in today’s rapidly changing world, yet research has shown that many learners need support for SRL. Recently, learning analytics has offered exciting opportunities for better understanding and supporting SRL. However, substantial endeavors are still needed not only to detect learners’ SRL processes but also to incorporate human values, individual needs and goals into the design and development of self-regulated learning analytics (SRLA). This paper aims to examine the challenges that lifelong learners faced in SRL, their needs and desirable features for SRLA.

This study triangulated data collected from three groups of educational stakeholders: focus group discussions with lifelong learners (n = 27); five teacher interviews and four expert evaluations. The groups of two or three learners discussed perceived challenges, support needs and willing-to-share data contextualized in each phase of SRL.

Lifelong learners in professional development programs face challenges in managing their learning time and motivation, and support for time management and motivation can improve their SRL. This paper proposed and evaluated a set of design principles for SRLA.

This paper presents a novel approach for theory-driven participatory design with multistakeholders that involves integrating learners, teachers and experts’ perspectives for designing SRLA. The results of the study will answer the questions of how learners’ voices can be integrated into the design process of SRLA and offer a set the design principles for the future development of SRLA.

To continue to stay relevant in the era of Industry Revolution 4.0 (IR4.0) alongside the unprecedented disruption of COVID-19, the importance of lifelong learning is indisputable though this concept has existed for decades. In this context, open and distance learning (ODL) institutions are urged to re-think and re-design their online learning support systems that inculcate self-regulated lifelong learning (SR3Ls) in their learners to be adaptable and resilient for the post-pandemic economy. The purpose of this paper is to develop a SR3Ls model, namely SR3Ls model by utilising the collective opinions of a panel of experts to determine the key domains and attributes.

A 2-round Delphi consensus study was conducted with 39 experts from five countries. The mean, standard deviation (SD), inter-quartile range (IQR) and the ratio of experts assigned score of 4 or greater were used as the basis of consensus assessment with criteria set at mean = 3.0, SD = 1.5, IQR = 1, ratio on score 4 or greater at = 75%. The questionnaire consisted of 5-point Likert-type scale rating the importance level of each attribute combined with open-ended questions.

This paper presented the findings of the first round of Delphi consensus study. For the first round, the experts were asked to evaluate 31 key attributes of SR3Ls model under five domains. The findings revealed that there were five key attributes to be eliminated from the list, while there were seven attributes identified as the key attributes with highest consensus. There were additional attributes suggested by the Delphi panel to be added in the second round of evaluation.

This international consensus-based SR3Ls model serves as an important benchmark for ODL institutions across the regions in developing meaningful and relevant online learning support systems for their learners to adopt SR3Ls attributes in order to meet the dynamic market demands.

Given that online search visibility is influenced by various determinants, and that influence may vary across industries, this study aims in investigating the major predictors of online search visibility in the context of blood banks.

To formalize the online visibility, the authors have found theoretical foundations in activity theory, while to quantify online visiblity the authors have used the search engine optimization (SEO) Index, ranking, and a number of visitors. The examined model includes ten hypotheses and was tested on data from 57 blood banks.

Results challenge shallow domain knowledge. The major predictors of online search visibility are Alternative Text Attribute (ALT) text, backlinks, robots, domain authority (DA) and bounce rate (BR). The issues are related to the number of backlinks, social score, and DA. Polarized utilization of SEO techniques is evident.

The methodology can be used to analyze the online search visibility of other industries or similar not-for-profit organizations. Findings in terms of individual predictors can be useful for marketers to better manage online search visibility.

The acute blood donation problems may be to a certain degree level as the information flow between donors and blood banks will be facilitated.

This is the first study to analyze the blood bank context. The results provide invaluable inputs to marketers, managers, and policymakers.

The Open University of Sri Lanka implemented a fully online professional development course on open educational resources-based e-learning (OEReL), which adopted a scenario-based learning (SBL) design within the constructivist pedagogy. It was designed to facilitate knowledge construction in a collaborative manner with the support of open educational resource (OER), mainly through peer-facilitated discussion forum activities. The purpose of this paper is to present a case study on how peer-facilitated discussions affected the OEReL process, what factors supported and hindered peer-facilitated discussions, and what challenges were faced during the process.

The OEReL course consisted of five modules with 14 discussion forum activities. Content analysis of the threaded forum discussions was the key data collection and analysis strategy based on the community of inquiry (CoI) framework (Garrison and Arbaugh, 2007). It was supplemented with participants’ reflections and focus group discussions.

The three elements of CoI – cognitive presence, social presence and teaching presence played a major role in knowledge construction in the OEReL process. A complementary relationship between cognitive presence, social presence and teaching presence was observed, where the three elements have interacted in supporting knowledge construction. Overall, the findings reaffirm the significant of role of instructors in cultivating the three presences within a peer-facilitated environment, by enabling learners to engage with the content in a meaningful manner through appropriate course design, structure and leadership.

Forum discussions created an opportunity for participants to engage in meaning making through social negotiation, where facilitation became a shared responsibility among instructors and learners. Peer-facilitation was the key strength that promoted critical, analytical and reflective thinking, as well as self-regulated learning. The SBL design, learning tasks with OER integration, and instructor guidance were the most supportive factors, while time constraints due to the participants’ workload was challenging.

Through carefully orchestrated, well-structured and pedagogically sound OEReL environments, peer-facilitated forum discussions can be designed creatively and implemented in a meaningful manner to enhance knowledge construction.

The purpose of the study was to test the usability of the MyLA app prototype by its potential users. Furthermore, the Web app will be introduced in the framework of “Mobile Learning Analytics”, a cooperation project between the Cooperative State University Mannheim and University of Mannheim. The participating universities focus on the support of personalized and self-regulated learning. MyLA collects data such as learning behavior, as well as personality traits. Last but not least, the paper will contribute to the topic of learning analytics and mobile learning in higher education.

For the empirical investigation, a mixed-method design was chosen. While 105 participants took part in the conducted online survey, after testing the app prototype, seven students joined an additional eye tracking study. For the quantitative part, a selected question pool from HIMATT (highly integrated model assessment technology and tools) instrument was chosen. The eye tracking investigation consisted of three tasks the participants had to solve.

The findings showed that the students assessed the idea of the app, as well as the navigation positively. Only the color scheme of the prototype was not very attractive to a noticeable amount of the participants. So, it requires slight modifications concerning the app design. For the eye tracking study, it can be stated that the students viewed the relevant parts, and they basically had no difficulties to solve the tasks.

Due to the empirical testing of the app prototype, the project team was able to adjust the application and to add further features. Furthermore, the backend was programmed and an additional tool (MyLA dashboard) was developed for lecturers. A mutual understanding of the targets, privacy issue and relevant features are indispensable for further development of the project.

This study explores ongoing research into self-mapped learning pathways that students utilize to move through a course when given two modalities to choose from: one that is instructor-led and one that is student-directed.

Process mining analysis was utilized to examine and cluster clickstream data from an online college-level History course designed with dual modality choices. This paper examines some of the results from different approaches to clustering the available data.

By examining how often students interacted with others, whether they were more internal or external facing with their pathway choices, and whether or not they completed a learning pathway, this study identified five general tactics from the data: Individualistic Internal; Non-completing Internal; Completing, Interactive Internal; Completing, Interactive, and Reflective and Completing External. Further analysis of when students used each tactic led to the identification of four different strategies that learners utilized during class sessions.

The results of this analysis could potentially lead to the creation of customizable design models that can assist learners as they navigate modality choices in learner-centered or less-structured learning design methodologies.

Few courses are designed to give the learners the options to follow the instructor or create their own learning pathway. Knowing how to identify what choices a learner might take in these scenarios is even less explored. Preliminary data for this paper was originally presented as a poster session at the Learning Analytics and Knowledge conference in 2019.