Online Learning Courses Research Articles

Online Learning Readiness Among University Students in Malaysia Amidst Covid-19

Universities around the world have been directly and indirectly affected due to the Covid-19 pandemic. Within the span of less than one month, the traditional face-to-face learning has been replaced by online learning to ensure education continuity. This paper sets out to examine online learning readiness among university students who have been thrown in at the deep end. It aims to investigate if demographic factors make any difference in their readiness to learn, online learning experiences and intention to continue using online learning. It also examines their preferred methods of online learning and challenges they face. Data collected from 399 students in two different online learning courses in Malaysia showed that respondents are generally ready for online learning. However, females are found to be more ready than male, degree students are more ready than diploma students while female students and degree students are more satisfied with online learning and have better learning experiences compared to male and diploma students. More than half of the respondents indicated that if given a choice, they do not want to continue with online learning in the future. Most respondents preferred online learning via pre-recorded lectures uploaded to Google Classroom and YouTube. While the biggest challenge for degree students is internet connectivity, for diploma students, it is the difficulty in understanding the content of the subject. Moving forward, government, telecommunication companies and universities should invest in developing internet infrastructure across the country as online learning will be the new norm in the foreseeable future. University also needs to provide further training to enhance academics’ online teaching skills to ensure lessons are delivered more effectively

Relationship between students’ online learning behavior and course performance: What contextual information matters?

This study examines whether including more contextual information in data analysis could improve our ability to identify the relation between students' online learning behavior and overall performance in an introductory physics course. We created four linear regression models correlating students' pass-fail events in a sequence of online learning modules with their normalized total course score. Each model takes into account an additional level of contextual information than the previous one, such as student learning strategy and duration of assessment attempts. Each of the latter three models is also accompanied by a visual representation of students' interaction states on each learning module. We found that the best performing model is the one that includes the most contextual information, including instruction condition, internal condition, and learning strategy. The model shows that while most students failed on the most challenging learning module, those with normal learning behavior are more likely to obtain higher total course scores, whereas students who resorted to guessing on the assessments of subsequent modules tended to receive lower total scores. Our results suggest that considering more contextual information related to each event can be an effective method to improve the quality of learning analytics, leading to more accurate and actionable recommendations for instructors.

Sviluppare ambienti inclusivi nella formazione universitaria online: esiti di una ricerca esplorativa.

This paper refers to the «Interdisciplinary Research Project» of the Department of Education at Roma Tre University. The title of the project is «E-learning for higher education: setting up an integrated model for the qualification of learning and educational relationships in online courses» and represents a development of a previous research (Bocci, 2019a), which was aimed at outlining some dimensions and issues of inclusive online education. Taking as a background the different theoretical perspectives that study inclusion and inclusive processes (such as the Bio-Psycho-Social Model, the Social Model, the Capability Approach and the Universal Design) in the present paper the authors show the results of an exploratory survey aimed at verifying the validity of a new search tool − an analysis form developed starting from the work of Grainne Conole (2013) on MOOCs − used to analyze the level of inclusion of some university online courses of the EduOpen platform. The aim of the work is to provide a self-analysis tool to better guide in an inclusive perspective those who design and deliver e-learning courses. The first results are encouraging and lead to further investment of resources in this direction.

Learning Technology Review: Vocabulary.com

Vocaburary.com (https://www.vocabulary.com/) is an application (hereafter app) designed to promote English vocabulary learning. The primary learning activities users can engage in with the app include: 1) taking short personalised online quizzes; and 2) learning or consolidating vocabulary by accessing immediate feedback. The website describes the strengths of learning vocabularies using the app by stating it as “the quickest, most intelligent way to improve vocabulary”. To help users to learn vocabulary efficiently, Vocabulary.com adopts “sophisticated algorithms” to choose the essential words for each user from over 14,000 words. Based on the results, the app then creates personalised quizzes for each user.
 In addition to the quiz, Vocabulary.com provides multiple functions to promote user vocabulary learning including: 1) online dictionaries; 2) vocabulary lists; 3) vocabulary games; 4) spelling practice while listening to the pronunciation; and 5) progress reports. The app provides both computer- and smartphone-based platforms (both iPhone and Android). The computer-based platform is free; whereas, users are required to purchase the smartphone-based platform. However, accessing the app via a smartphone allows users to use their downtime efficiently to learn English vocabulary anytime and anywhere. “Educator Edition” provides educators with useful functions to promote online and blended learning courses, including the capability to monitor the progress of each learner on the platform.

Educating at Scale for Sustainable Development and Social Enterprise Growth: The Impact of Online Learning and a Massive Open Online Course (MOOC)

The solutions to the grand challenges of sustainability, poverty, and health affecting the world will require education and capacity building for all individuals implementing change on a global scale. The challenge ahead is to reach those missed by traditional education and support networks. Online Learning and Massive Open Online Courses (MOOCs) have the potential to build knowledge and share best practice experiences among individuals worldwide. This paper examines the case of the FutureLearn Social Enterprise Program, a series of MOOCs with over 50,000 registered learners, of which 15% become active learners, engaging in online exercises, debates, and conversations. This paper draws on quantitative and qualitative data collected over four years. The findings show that the course has not only had an impact on the creation of new startup social enterprises, but it has also supported a large proportion of learners in developing sustainability and social entrepreneurial ideas within a range of organisations in the public, private, and civil society sectors. The findings also show a positive cascading impact effect from the learners registered on the course to those in their network, as ideas are shared, and learners become mentors to others. Our conclusions demonstrate how digital education and online courses contribute to global education for sustainable development and social enterprise development.

Cognitive optimism of distinctive initiatives to foster self-directed and self-regulated learning skills: A comparative analysis of conventional and blended-learning in undergraduate studies

Independent learning in massive open online courses (MOOCs) requires considerable effort from the learners themselves. Blended-learning has been recognised to foster independent learning among undergraduate students. With the popularity of the blended-learning approach to teach in traditional educational settings, little has been mentioned on how cohesive this approach is in fostering self-directed learning and self-regulation among university students. This study hopes to explore undergraduate learners in their distinctive study patterns. The study was conducted to investigate a comparative study between students from two departments; Science and Social Science. The aim was to explore the students’ self-directed and self-regulated learning skills in conventional classrooms and aspects of blended-learning embedded in a MOOC platform in two academic years for undergraduates at a top UK university. This study encompasses two case studies; firstly, a combine blended-learning seminar and a conventional seminar classes and a study undertaken with a student of English as a second language (ESL). The blended-learning students were participants who registered in a conventional university and took an optional module in computer security. The second group of students participated in a core module of logic and verification. The second case study was with a final year undergraduate student in Education Studies. The students studied and engaged with the course content using their initiative and directing their learning approaches.

Review of Self-Regulated Learning in Massive Open Online Course

The research is financed by Chinese Production and Research Project (Project ID: 201901297003); Hubei Provincial Department of Education’s Research Project on Teaching Reform in Colleges and Universities (Project ID:2017376);Chinese University Students’ Project on Innovation and Entrepreneurship Project ID:S201913256032);Hubei Normal University’s Research Project on Teaching Reform (Project ID: 2019013). Abstract Over the last decade, much attention has been paid the effects of self-regulated learning (SRL) in massive open online courses (MOOCs). However, a systematic understanding of the topic is rather limited. This study drew a general outline of important factors affecting the SRL in MOOCs. The study summarizes two important SRL modes as the theoretical basis. Then, the study analyses the motivational, metacognitive and cognitive regulation strategies, and behavioural regulation strategies which affect SRL in MOOCs. Finally, suggestions for future research in MOOCs are offered. Keywords: self-regulated learning , MOOCs, mode , SRL strategies DOI: 10.7176/JEP/11-8-02 Publication date: March 31 st 2020

Detecting the Depth and Progression of Learning in Massive Open Online Courses by Mining Discussion Data

In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or posting questions, but no solution has yet been provided so that instructors can track the progress of the learners using a validated framework from education research. In this paper, we develop a model to automatically label a post based on the first phase of the interaction analysis model (IAM). This allows instructors to automatically identify whether students are stating opinions, clarifying details, or engaging in activities such as providing examples to peers. Our model is tested on a Coursera MOOC devoted to Chemistry, for which we are able to correctly categorize the IAM status in 4 out of 5 posts. Our approach thus provides instructors with an intelligent system that generates actionable learning assessment data and can cope with large enrollment. Using the system, instructors can quickly identify and remedy learning issues, thus supporting learners in attaining their intended outcomes.

Self-directed learning in MOOCs: exploring the relationships among motivation, self-monitoring, and self-management

Given that massive open online learning courses (MOOCs) are considerably different from traditional classrooms in terms of roles and responsibilities of instructors and learners, successful learners are required to be self-directed in MOOC learning environments. One of the most popular self-directed learning (SDL) models proposed by Garrison (Adult Education Quarterly 48(1):18–33, https://doi.org/10.1177/074171369704800103 , 1997) includes three components: motivation, self-monitoring, and self-management. This model was originally discussed from traditional online and face-to-face learning environment. Thus, the present study investigated the relationship among motivation, self-monitoring, and self-management in MOOCs by surveying 322 MOOC learners. Using structural equation modeling, this study found that motivation directly affected self-monitoring and indirectly influenced self-management through self-monitoring. In addition, self-monitoring positively influenced self-management. Therefore, promoting student self-monitoring skills and motivating students is critical. Additional research is needed on the ways to facilitate and support self-monitoring of MOOC learners. Future research could examine the influence of the three elements of SDL on learning achievement and engagement. In addition, further exploration of learner behaviors in MOOCs could provide insights on facilitating learners’ SDL.

Online Learning Design At Higher Education: An Example From Mathematics Classroom

The rapid increase of technological consumption in many aspects has left educational institutions a great demand to apply it, including higher education. At higher education, the lecturers generally undertake the teaching and learning process out of class. In this case, one possible approach to facilitate this distant learning is through virtual classroom (online learning). The potential use of online learning rises the needs towards how it should be designed. Thus, this paper attempts to discuss about designing online learning that can help enhance student learning and make them engage with the content. An example of classroom implementation was depicted from Mathematics course. The data were collected through an analysis of developmental study conducted at two Indonesian universities. The results of this study indicate that there are four main concerns in designing constructive online learning (1) course arrangement; (2) content appearance; (3) collaborative and interactive; and (4) well-timed response.

Andreas Rio Adriyanto MEMAHAMI PERILAKU GENERASI Z SEBAGAI DASAR PENGEMBANGAN MATERI PEMBELAJARAN DARING

Virtualization in learning provides a barrier between students and lectures. The existence of a digital partitioncreating a boundary that gives freedom of students to collect data and information. Previous studies haveshown the low engagement on students in completing online learning courses. Although there are still weaknesses,the implementation of online learning is a necessity. Students who will use this online learning aregeneration Z. They were born in the period of 1997-2012 when computer technology and the internet haddeveloped. They are more familiar with the concept of digital information technology before getting to know theconcept of school. This generation is also referred to as digital natives. This research uses literature studiesand surveys on digital generation in relation to their digital activities. The results of this study are expected tobe one source of understanding the behavior of Generation Z as the basis of developing online learningmaterials.

Using clickstream data to measure, understand, and support self-regulated learning in online courses

The ability to regulate one's own learning is essential for success in online courses. Recent efforts have used clickstream data to create timely, fine-grained, and comprehensive measures of self-regulated learning (SRL) in online courses in an attempt to shed light on the process of SRL and to improve the identification of students who lack SRL skills and are at risk of low achievement. However, key questions remain: to what extent do these clickstream measures correspond to traditional self-reported measures about specific SRL constructs? Do these clickstream measures provide more information than existing self-reported measures in predicting course performance? This study used the clickstream data collected from a learning management system to measure two aspects of SRL: time management and effort regulation. We found that the clickstream measures were significantly associated with students' self-reported time management and effort regulation after the course. In addition, these clickstream measures significantly improved predictions of students' performance in the current and subsequent courses over predictions based on self-reported measures alone. These results provide evidence for the validity of the clickstream measures and guide the use of clickstream data to understand the process of SRL and identify students who might not be well served by taking classes online.

Online learning performance and satisfaction: do perceptions and readiness matter?

ABSTRACTThe current study proposes a comprehensive structural model to determine whether online learning perceptions and online learning readiness affect students’ online learning performance and course satisfaction. A questionnaire was voluntarily completed by 356 undergraduate students enrolled in a cross-campus, general education, asynchronous online course in Taiwan. The structural equation modeling analyses indicated that students’ computer/Internet self-efficacy and motivation for learning exerted a direct, positive effect on their online discussion score and course satisfaction. Furthermore, it was found that students’ computer/Internet self-efficacy for online learning readiness had a mediated effect not only on online learning perceptions and online discussion score but also on online learning perceptions and course satisfaction. The findings of this research are helpful for both academics and practitioners of online learning to design online courses that particularly emphasize computer/Internet self-efficacy.

Best Practices in Project-Based Learning

A retrospective case study design was used to analyze online instructional technology courses at two US universities. A project-based learning design model was used for both complete online delivery and emergency remote teaching formats. Although deep areas of scholarship exist for online learning, project-based learning, and digital media literacies, research in the area of project-based learning designs to support technical learning in online courses is nascent. A review of these areas of literature is presented, and results from this case analysis are presented as recommendations to faculty who wish to design project-based learning for online technical courses, or for those who are planning emergency remote teaching conversions for similar technical courses.

Structure and Delivery for Mobile Learning Experiences

The purpose of this article was to identify, implement, and evaluate the effectiveness of best practices from the mobile learning literature for the structure and delivery of mobile learning. Mobile learning activities were deployed in a videoconference equipment training course which was accessed by physicians, nurses, and healthcare professionals at medical organizations across Ontario. With regards to mobile learning delivery, user flexibility and control were identified as critical when utilizing a mobile learning experience to apply knowledge in a specific learning context. Avatar hosts were also identified as effective feedback and guidance mechanisms. The informal structure of mobile learning proved to be ideal for contextual, hands-on learning of specific workplace skills, supported by the baseline and summative knowledge provided by the online learning course. This study found that the structure and delivery of mobile learning must be considered during the instructional design stage in order to provide practical learning experiences and reliable learning outcomes.

Transformation toward e-learning: experience from the sudden shift to e-courses at COVID-19 time in Central European countries; students’ satisfaction perspective

This study aims to evaluate transforming toward online-learning, concerning students’ satisfaction, social presence and students’ intention to continue with e-learning in Central European countries, taking the case of Hungarian higher education online courses during COVID- 19 measures. This study finds that masters and undergraduate students’ satisfaction and social presence of online learning courses are neutral with little bias to be positive, also satisfaction has the key role in affecting student’s intention to continue with future online-learning.

Towards an Adaptive E-learning System Based on Q-Learning Algorithm

The challenge for today’s online learning systems is to provide effective access to knowledge and content that is relevant to learners’ expectations. The majority of these systems lack methods to support the needs of learners who are generally heterogeneous in terms of intellectual abilities, learning pace, preferences, etc. There is a need to provide powerful mechanisms to organize such learning and to adapt pedagogical decisions to the particular skills and needs of each learner. Our contribution in this area of research is the development of an adaptive e-learning system that can generate learning paths adapted to the profile of the learner. Indeed, we propose an approach to dynamically compose adaptive online learning courses based on learner activities, learning objectives, and instructional design strategies using the Q-learning algorithm, which is a reinforcement learning technique. The latter is based on the behavior of the learners and provides the course content necessary to achieve the learning objectives according to the positive and or negative feedback of the learners. In addition, we conclude with experience and evaluation of our approach based on the Q-learning algorithm.

IoTs for Data Collection and Trends Prediction of Online Learning Courses

The rapid growth of educational data mining (EDM) is an emerging field in the academic world of research and studies focusing on collection, archiving, and analysis of data related to delivery methodology, quality of materials and student learning and assessment. The information analyzed informs the learning institution on how to improve learning experiences and how to run the institutional effectively. The people responsible for making decisions in the learning institution will able to make informed data-driven decisions. This paper explores the value of the Internet of Things (IoT) in capturing and mastering massive data for online courses to assess and identify typical learning scenarios for learners. We hope this would be a useful instrumental tool for the range of approaches in education institutions to help their struggling learners to succeed in the academic field.

New Digital Education as the Market Solution to the Student Debt Crisis

I investigate social interest, or hype, in online learning. The two datasets of interest are derived from public search engine data for the United States over the period 2000-2020. This data is assessed for hype cycle dynamics. I find that interest in online learning and massive online open courses follow well-defined hype cycles. Interest in online learning has recovered from a low point. This indicates economic durability and positive growth outlook from an institutional point of view. I describe the history of online education as proceeding in three ages. New Digital Education is an affordable, employer-lead, hybrid learning approach to accredited higher education. New Digital Education emerges during the Second Age, from 2012-2017, and is normalized in the Third Age, from 2018 through the present. New Digital Education constitutes a sustainable market solution to the student debt crisis. A market solution to the student debt crisis undercuts the need for policy action.

Renewable energy remote online laboratories in Jordan universities: Tools for training students in Jordan

The use of the concept of technology-enhanced learning is a design already applied in developed countries and incorporated as an active part of their educational models and curricular development. This is even more relevant in the case of eLearning, where these technologies correspond to remote/virtual laboratories. They are very useful in the fields of Science and Engineering. According to this, the current work shows the incorporation of this type of technology to traditional curricular schemes, with the aim of improving the effectiveness of learning. Another objective is to build reusable infrastructures among Universities, supported with public and private government resources. Specifically, this paper shows the development, implementation, and integration of remote renewable energy laboratories in Jordan, and how they have been used within the director plan of the Jordanian government for the promotion of renewable energies in that country. This plan includes not only the design of remote laboratories but also their integration into a curricular model. This integration is done at the level of online learning courses and pilot experiences in the development of these types of learning technologies. In a distance methodology environment, the instructors must design the course structure keeping in mind that students are online, but not face-to-face in the classroom. Additionally, they have to propose adapted resources (remote laboratories, guidelines, etc.) and content.The paper focuses on the incorporation of remote/virtual laboratories, showing how these labs were developed/integrated into online courses. To validate the incorporation of this type of resources in an environment usually not online, a set of surveys was designed to support a technology evaluation methodology (TAM, Technology Acceptance Model). This evaluation allows knowing the degree of satisfaction of the technology (remote and virtual laboratories as resources) using a structured experimental method (SEM, Structural Equation Models). As a result of the application of this experimental method, the calculated statistical data indicate that the use of remote and virtual laboratories improves the perception and use of virtual environments at a distance. Also, it can be indicated that these laboratories are presented as an essential resource to improve the quality of online teaching in engineering courses.