A Model for Scaffolding Traditional Distance Learners in Africa for Constructivic Online Learning

Recently, education has changed from physical learning to online and hybrid learning. Furthermore, the outbreak of COVID-19 makes them more significant. An online learning management system (LMS) is one of the most prevalent approaches to online and distance learning. The acceptance of the students towards the LMS is significant and it can give either bad or good responses to ensure the success of LMS. However, the Universiti Tun Hussein Onn Malaysia (UTHM) has not yet implemented any study to examine their LMS. The Unified Theory of Acceptance and Usage of Technology (UTAUT2) model is used in this study to investigate students’ Behavioral Intention and Use Behavior when using the LMS in UTHM. This study also introduces a new construct in UTAUT2 named Online Learning Value. 376 respondents took part in this survey. Descriptive Statistics, Reliability Analysis, Pearson Correlation Coefficient, and Multiple Linear Regression analysis were all used to analyze survey data. The outcome of this research is Performance Expectancy (β=0.129, p=0.014), Hedonic Motivation (β=0.221, p=0.000), Online Learning Value (β=0.109, p=0.036) and Habit (β=0.513, p=0.000) has influence on students’ intention to use LMS. Besides that, Facilitating Conditions (β=0.481, p=0.000) are the most important factors in students’ use behavior toward the LMS followed by Habit (β=0.343, p=0.000) and Behavioral Intention (β=0.239, p=0.000). By utilizing the UTAUT2 model, the constructs of technology acceptance related to students' adoption of LMS have been identified and may become a reference to the stakeholders for future enhancement.

Following the rapid development of open distance education and the enrichment of online resources and Learning Management Systems in Asia, the quality of interactions amongst learners and online content, teacher and peers has become one of the imperative factors in determining the efficacy of web-based teaching-learning. Online learning is distinctive as compared to face-to-face interaction in terms of how the course material is presented, the nature of interactions, and overall learning experience. This case study explores the understanding, expectation and experience of learners from China and Malaysia based on vital aspects of learning in the web-based environment such as the concept of teaching and learning, the role of the teacher, communication patterns in the virtual classroom, relationships with the teacher and the classmates, and attitudes towards learning achievement. These are reflected in the learning patterns and behavior of online learners as observed in their interaction with the web-based content and participation in the online forum discussions within the online Learning Management Systems. In addition, this case highlights the influence of national culture towards learners’ interaction as displayed in their online learning activities.

Following the rapid development of open distance education and the enrichment of online resources and Learning Management Systems in Asia, the quality of interactions amongst learners and online content, teacher and peers has become one of the imperative factors in determining the efficacy of web-based teaching-learning. Online learning is distinctive as compared to face-to-face interaction in terms of how the course material is presented, the nature of interactions, and overall learning experience. This case study explores the understanding, expectation and experience of learners from China and Malaysia based on vital aspects of learning in the web-based environment such as the concept of teaching and learning, the role of the teacher, communication patterns in the virtual classroom, relationships with the teacher and the classmates, and attitudes towards learning achievement. These are reflected in the learning patterns and behavior of online learners as observed in their interaction with the web-based content and participation in the online forum discussions within the online Learning Management Systems. In addition, this case highlights the influence of national culture towards learners’ interaction as displayed in their online learning activities.

The dynamic business environment and powerful market forces in the 21st century are challenging leaders at open universities to compete successfully in the national and global higher education stage. The notion of quality is becoming an important and overriding issue with the paradigm shift in the education landscape due to the rapid penetration of Internet usage. Open universities are experiencing pressure from numerous stakeholders to become more client-focused, particularly in their provision of technology-enhanced education to systematically support the learning experience of open distance learners. In the pursuit of establishing institutional and national/regional-based quality assurance practices, Asian open universities should pay particular attention to one of the key components within the overall QA framework; that is, the web-based teaching and learning on the online learning management system (LMS). The assurance of quality in the web-based teaching and learning component is vital to support the effective and efficient delivery of open and distance education within the blended approach adopted by many open universities. In this study, the authors first examine the dimensions of quality assurance of key services that are closely associated with web-based education in the online LMS of Wawasan Open University (WOU). The authors then analyse the pattern of interactions in the LMS to determine the actual activities of learners in the web-based environment. By synthesising the findings, indicators that address diverse facets and components of quality relevant to web-based teaching and learning in the LMS are identified. The authors then discuss the application of the quality components within the overall QA framework in WOU to further enhance the quality of its web-based teaching and learning component. Assessment of learners' satisfaction in WOU is carried out to determine the effectiveness of the QA components in the LMS. The QA components identified in the web-based teaching and learning within the LMS are then recommended to Asian open universities for integration into their overall QA framework.

This study examined perspectives of distance education students on online learning based on their access gadgets (availability and functionality), online presentation or teaching methods, actual use of online learning coupled with its challenges. A quantitative approach and descriptive survey design were adopted for the study. A sample of 1061 was drawn from a study population of 44,134 distance learners across sixteen administrative regions and data collected using a questionnaire. Partial least squares structural equation modelling (PLS-SEM) was used to analyse the hypotheses of the study, and descriptive statistics were deployed to analyse students perceived challenges. The study found a statistically significant relationship between the availability and functionality of online gadgets, availability of online gadgets and online presentation methods, functionality and online presentation methods and functionality and online learning usage. Thus, these factors are necessary for successful online learning. Four main perceived challenges identified were unreliable power/electricity and internet connectivity, lack of collaboration and motivation during online learning. Therefore, it was recommended that steps are taken to resolve the perceived challenges while adopting the blended approach comprising face-to-face and online learning. The blended learning approach would enable students to adjust better and appreciate its usefulness in distance education.

INTRODUCTION
 Student performance prediction has become a viable means to improving academic performance and course content in online learning. Predictive models such as neural networks, decision trees and linear regression are used to transform inputs (e.g. past performance, social background, learning system usage patterns, test results) into outputs (course completion, expected grade, difficulties encountered, personalized suggestions). Often, the existing quantitative data drive model design, especially when applying such models to the conventional classroom and the person delivering the course, is a passive participant in designing models and delivering data.
 In seeking to capture and code as much student behavior and environment as possible to apply learning analytics to a mostly conventional classroom, the most successful inputs (predictors) among existing models can be identified, categorized and their common characteristics determined. Together with a study of formative and summative assessment methods (e.g. types of feedback and how it can be captured) and factors affecting student performance in the classroom (e.g. environmental factors), this allows to identify the existing data in classrooms that are not captured by current learning management systems, thus allowing the expanded use of learning analytics and student performance prediction in traditional classrooms, with a focus on personalized suggestions.
 The goal of the paper is to identify patterns among inputs used in existing models of student learning (based on online learning and learning management system data mining) that can then also be applied to the traditional classroom.
 Research question: how can characteristics common to effective predictors of student performance be used to identify predictors among data produced in the traditional classroom?
 MATERIAL AND METHODS
 A literature review is performed where inputs captured and features discovered in existing learning analytics systems are characterised, along with methods used to identify those and the modelling approaches employed.
 An attempt is made to identify measures in online learning that may have analogues in the traditional classroom (e.g., seating patterns and communication in chatrooms) or for which proxies may be found (e.g. screen size and lighting quality, where the proxy is the classroom number).
 The corresponding outputs are recorded where possible, with a focus on those that allow providing feedback for individual students or for course/curriculum deliverers/designers (i.e. allow to improve the success of future students in this course).
 RESULTS
 Successful predictors and characteristics common to those are identified, so that they can be used in features engineering for student performance prediction models.
 Predictors used in online learning are categorised, so that analogous inputs can be developed for use in traditional classrooms.
 Types of feedback provided by existing models of learning are identified, where possible, along with the corresponding input (weights of inputs).
 Studies are identified where learning personnel, not the researcher, were able to drive the model development process.
 DISCUSSION
 Recently, there has been increasing focus on increasing the visibility into models of learning and of involving learning personnel in designing, modifying and running those models. Providing inputs and recognizing the features they represent determines the success of such models. Therefore, recognizing existing successes and applying them to formative assessment methods may be a means of recognizing additional inputs to and features used in models, while involving educators. Applying learning models to the traditional classroom as an integrated part of the learning management (school record keeping/grading) systems may allow to expand their use, while simultaneously increasing the predictive power and effectiveness of (personalized) suggestions, both by using existing data, and by providing tools for educators to transform the existing feedback they provide into data than can be used as inputs for models.
 CONCLUSION
 Predictors used in learning models in online learning can be applied to the traditional classroom. Analogues may be found for predictors that are not available in the conventional classroom. Common characteristics and categorisation of predictors may be used to identify predictors among existing data, including data provided by students (e.g. formative feedback) that is not captured by the existing learning management systems used.

INTRODUCTION Student performance prediction has become a viable means to improving academic performance and course content in online learning. Predictive models such as neural networks, decision trees and linear regression are used to transform inputs (e.g. past performance, social background, learning system usage patterns, test results) into outputs (course completion, expected grade, difficulties encountered, personalized suggestions). Often, the existing quantitative data drive model design, especially when applying such models to the conventional classroom and the person delivering the course, is a passive participant in designing models and delivering data. In seeking to capture and code as much student behavior and environment as possible to apply learning analytics to a mostly conventional classroom, the most successful inputs (predictors) among existing models can be identified, categorized and their common characteristics determined. Together with a study of formative and summative assessment methods (e.g. types of feedback and how it can be captured) and factors affecting student performance in the classroom (e.g. environmental factors), this allows to identify the existing data in classrooms that are not captured by current learning management systems, thus allowing the expanded use of learning analytics and student performance prediction in traditional classrooms, with a focus on personalized suggestions. The goal of the paper is to identify patterns among inputs used in existing models of student learning (based on online learning and learning management system data mining) that can then also be applied to the traditional classroom. Research question: how can characteristics common to effective predictors of student performance be used to identify predictors among data produced in the traditional classroom? MATERIAL AND METHODS A literature review is performed where inputs captured and features discovered in existing learning analytics systems are characterised, along with methods used to identify those and the modelling approaches employed. An attempt is made to identify measures in online learning that may have analogues in the traditional classroom (e.g., seating patterns and communication in chatrooms) or for which proxies may be found (e.g. screen size and lighting quality, where the proxy is the classroom number). The corresponding outputs are recorded where possible, with a focus on those that allow providing feedback for individual students or for course/curriculum deliverers/designers (i.e. allow to improve the success of future students in this course). RESULTS Successful predictors and characteristics common to those are identified, so that they can be used in features engineering for student performance prediction models. Predictors used in online learning are categorised, so that analogous inputs can be developed for use in traditional classrooms. Types of feedback provided by existing models of learning are identified, where possible, along with the corresponding input (weights of inputs). Studies are identified where learning personnel, not the researcher, were able to drive the model development process. DISCUSSION Recently, there has been increasing focus on increasing the visibility into models of learning and of involving learning personnel in designing, modifying and running those models. Providing inputs and recognizing the features they represent determines the success of such models. Therefore, recognizing existing successes and applying them to formative assessment methods may be a means of recognizing additional inputs to and features used in models, while involving educators. Applying learning models to the traditional classroom as an integrated part of the learning management (school record keeping/grading) systems may allow to expand their use, while simultaneously increasing the predictive power and effectiveness of (personalized) suggestions, both by using existing data, and by providing tools for educators to transform the existing feedback they provide into data than can be used as inputs for models. CONCLUSION Predictors used in learning models in online learning can be applied to the traditional classroom. Analogues may be found for predictors that are not available in the conventional classroom. Common characteristics and categorisation of predictors may be used to identify predictors among existing data, including data provided by students (e.g. formative feedback) that is not captured by the existing learning management systems used.

It is noted that in modern conditions the issue of online education development in Ukraine has become especially acute, in particular, in the development of a long-term program to improve secondary and higher online education and ensure its new level of quality. The article is devoted to determining the need for distance and online education, the differences between them, the necessary forms of communication, the advantages and disadvantages of these forms of education, as well as prospects for distance and online education in Ukraine. It has been identified that online and distance education is viable and effective teaching strategies, but each has its own clear advantages and disadvantages for both teachers and students. The article proves that there are the following differences between these types of education: the location of the teacher and students; interaction between teacher and students; intention of teaching strategy. The authors list the advantages of distance education: distance education can continue without interruption, even in cases such as emergencies or the COVID-19 pandemic; distance education provides more flexibility for students to work at their own pace and review assignments as needed. The article summarizes the main forms of online communication between students and teachers - video conferencing, forum, chat, blog, etc. In addition, the most common web resources for distance education: Moodle, Google Classroom, Zoom and others. The problems that arise in the implementation of distance education have been identified: it is impossible to use distance education if students do not have access to devices or the Internet at home; it is difficult to keep a real contribution of the student to the work; distance education can make falsification even easier than online education; distance education can lead to even more screen time for students. It was concluded that the use of the Internet in teaching is necessary both for teachers who seek to offer their students different ways of learning, and for the students themselves. It has been proven that distance education is most useful for those students who have constant access to technology at home and work responsibly and independently, and it has a clear advantage in the event of an unexpected restriction of classes in the free economic zone.

Background There has been a rapid development and adoption of online learning in medical education. However, it is difficult to adopt the currently available online learning management systems (LMS). This study aimed to examine learners’ perspectives on the evaluation of online LMS. Methods An online LMS was developed based on the evidence-based guidelines. Two cross-sectional studies were conducted. A short survey was conducted with 716 learners registered on the LMS to obtain their perspectives on the online participation. A satisfaction survey was conducted with 255 learners enrolled in the courses taught solely online. Data from the LMS monitoring system was used to report the uptake of online courses. Data were analyzed using descriptive statistics. Results Participants reported that the major factor influencing LMS uptake was the ability to be accessed anytime and anywhere (n = 556, 77.7%). The participants had good experience in using the LMS and were satisfied with it (n = 255, mean = 4.53, SD = 0.62). For online degree courses, the course had a high completion rate of 90% provided that a mark was assigned for course attendance. For non-degree courses, irrespective of whether they were free, paid, exam-based, or participation only, the completion rate was considered low (range 4.3–36.7%). Conclusion Under a limited budget, a medical school in a low- to middle-income country could develop an effective online LMS to meet learners’ needs. Our newly developed online LMS is relevant, accepted and to the satisfaction of the learners. Medical schools in the same context are encouraged to develop their own online LMS that serve and support learning in both degree and non-degree courses.

One significant innovative technology to expand teaching and learning mostly in Distance Education is Learning Management System (LMS). LMS allow learning institutions to offer a larger number of courses online whether full or blended, by providing institutions with a digital space for numerous purpose which includes documentation, tracking and online training. However, for the relevance of LMS within an education context, distance learners’ attitudes towards the use of LMS must be investigated. The study therefore aimed at examining the Attitude of Distance Learners towards the Utilization of LMS (A case study of the National Open University of Nigeria). Data were collected from 697 respondents using a research adapted questionnaire. Data collected for the study were analyzed using mean and standard deviation to answer research question one while hypotheses one and two were tested using independent t-test and ANOVA respectively. The findings indicated that there was a significant difference between male and female distance learners on their attitude toward the use of LMS. Thus, no significant difference existed among science, arts, and social science distance learners’ attitude towards the use of LMS. It was therefore recommended that efforts should be made to ensure that distance learners do not just have a positive attitude towards the use of LMS but should be taught the value of LMS to ensure its effective utilization.

Use of signaling to integrate desktop virtual reality and online learning management systems

Teacher education through Open and Distance Learning (ODL) mode is a collaborative effort to support the quality teaching and learning with integration of Information and Communication Technologies (ICTs) in present word. It is a challenge to explore effective and efficient utilization of technologies to ensure meaningful learning of distance learners. Research and development in the field of ODL system is a means to improve pedagogical practices with meaningful integration of ICTs. In the present world technology has emerged as a powerful means of learning in face-to-face mode and ODL system as well. Utilisation of technology is not just limited to classroom teaching learning process. It has extended beyond the four walls of classroom to facilitate and promote student learning of learners in the ODL system. This technology mediated interventions has multiplier effort for providing better access, quality and equality in terms of providing services to all. IGNOU is emerged as a leader in the field of ODL system in our country in terms of bringing innovations in designing and developing technology enabled learning environment for training & orientation of teachers through ODL mode. In ODL system of IGNOU, the key is to promote collaborative learning, leading to a move towards autonomous learning. IGNOU pays an important role in the field of teacher education at national level through ODL system. IGNOU contributed training of 25510 (B. Ed) and 983 (M. Ed) teachers in the year 2015. B. Ed and M. Ed Programmes of IGNOU attracted large number of students in the country in the field of teacher education. Despite of all initiatives, it’s true that we have a long way to go in terms of effective and efficient implementation of technology mediated interventions with an appropriate Learning Management System (LMS) for our distance learners. This demands capacity building of teacher educators, teachers, student teacher, academic administrators and leaders to adapt to new technology in view of diversities of all kind of our distance learners. Commitment of people associated with the collaboration for effective implementation of programmers through ODL mode is important. The present paper is an attempt to explain the potentials of ODL system of IGNOU in the field of teacher education in our country. Attempt has been made to analyze the trends in enrolment of students (2001-2015) admitted in B. Ed and M. Ed Programmes of IGNOU and challenges in terms of maintaining the quality of implementation of the programmes in ODL system and addressing to the issues of equity and quality at national lrvel. It would be a source of rich experience to bring evaluation in teacher education programmes offered through in ODL mode in our country to further revamp it, keeping in view of needs and expectations of distance learners of our country. The paper covers aspects such as; i) issues in hand; ii) context of the study; iii) enrolment trend in terms of gender, area, category; iv) major challenges; and v) implication. It would provide a base/foundation for taking further research in the field of ODL system in teacher education and how best integration of technology in general and web based technology in particular be made meaningfully for all functionaries in the field of teacher education in our country.

Despite the fact that distance education developed in the 90s of the XX century in most countries, now this type of learning is very relevant because of the events taking place in Ukraine. The aim of this paper is to analyze distance learning with its all peculiarities and features, to compare it with online and virtual learning as it is often associated with online and virtual learning. However, these are different concepts. Distance learning has a more detailed design of the lesson and has a relatively clear structure, such as: setting the lesson, goals, assessment of students’ understanding of the lesson material, the content of the lesson, assessment of mastery of the lesson, time frame of the lesson. Tasks should be clear, useful, and understandable. Distance learning, unlike online one, which has emerged as a result of the spread of the coronavirus pandemic, is more thoughtful and active. It is flexible, teaches independence, and expands the capabilities of both teachers and students. The main difference between distance learning and other types of learning is that online learning is the acquisition of knowledge and skills through gadgets connected to the Internet in the “here and now” mode and this format is a continuation of distance learning. Apps like Face Time, Google Hangouts, Skype, Microsoft Teams, Zoom or What’s App can be used to provide these synchronous connections. Among the advantages of distance learning are individualization of learning topics, accessibility, individual consultation with the teacher, effective feedback, ease of viewing and processing the lesson material and others. Distance learning is a multifaceted concept, because it can be understood as anything – sending tasks, tests and independent work. It can be both synchronous and asynchronous, completely independent, or with the support of the teacher at certain stages. Keywords: distant learning, virtual learning, online learning, synchronous and asynchronous learning, independent work.

In recent years, social networking websites play a very important role as the interactive platform between users as well as lecturers and learners. Thus, it would be a good idea if a learning management system can be built based on those social networking websites, such as Facebook. In this paper, we therefore proposed to construct an online learning and course management system, which can transform traditional learning management system functions to enable better interactions between lecturers and learners. Furthermore, the system has been implemented and the functions will be shown in the paper. We also concluded this paper with some future directions and suggestions about e-learning, learning management systems and social networking website.

Strengthening Online Education Approaches in Institutions of Higher Learning