An adaptive hybrid MOOC model: Disrupting the MOOC concept in higher education

Most university degrees often require students to demonstrate proficiency in mathematics, which is the basic requirement in many fields, such as science, engineering, or technology. Mathematical knowledge is so common as to be essential in higher education. Although mathematical skills are crucial to the success of study in many domains, a large number of students are not willing to study related courses. Anxiety and pressure triggered by previous failures in mathematic learning are considered as the reason. The online learning environment provides students with opportunities to exchange opinions with others and facilitate their self-regulated learning. Scholars believe that the learning performances of students can be enhanced if they make reference to other students' learning strategies during the study process. The practice of making references to other students' learning strategies and mutually monitoring each other during the study process is called social regulation. The study efficiency of social regulation in learning mathematics will need to be verified. This study has adopted a social regulation-based online learning approach for assisting students in achieving learning goals with peers' power. At the same time, this study conducted an experiment with an experimental group and a control group. The social regulation-based online learning approach was used by the experimental group while the conventional self-regulated learning approach was used by the control group. According to the results, the social regulation-based online learning approach enhances students' learning achievements and learning motivations in mathematics. Based on the results of the sequential pattern analysis for investigating the online learning behaviors of the two groups of students, students who use the social regulation-based online learning approach have more positive online learning behaviors, such as reading the supplementary materials regarding the wrongly answered questions and revising the notes. On the contrary, students who use the conventional self-regulated learning approach only pay attention to the results of tests and feedback provided by their teacher. They seldom have behaviors of looking at the supplementary materials, adding or deleting notes. With the above verification, the developed system of this study not only enhances students’ learning performances, but also guides them to have more meaningful learning behaviors in mathematics.

Effects of a social regulation-based online learning framework on students’ learning achievements and behaviors in mathematics

In recent years there has been an enormous increase in learning resources available online through massive open online courses and learning management systems. In this context, personalized resource recommendation has become an even more significant challenge, thereby increasing research in that direction. Recommender systems use ontology, artificial intelligence, among other techniques to provide personalized recommendations. Ontology is a way to model learners and learning resources, among others, which helps to retrieve details. This, in turn, generates more relevant materials to learners. Ontologies have benefits of reusability, reasoning ability, and supports inference mechanisms, which helps to provide enhanced recommendations. The comprehensive survey in this paper gives an overview of the research in progress using ontology to achieve personalization in recommender systems in the e-learning domain.

Review of ontology-based recommender systems in e-learning

In personalized learning, each student gets a customized learning plan according to their pace of learning, instructional preferences, learning objects, etc. Hence the content recommender system in Personalized Learning Environment (PLE) should adapt to learner attributes and suggest appropriate learning resources to aid the learning process and improve the learning outcomes. This systematic literature review aims to analyze and summarize the studies on learning content recommenders in adaptive and personalized learning environments from 2015 to 2020. The publications were searched using proper keywords and filtered using the inclusion and exclusion criteria, which resulted in 52 publications. This paper summarizes the recent trends in research on different aspects of the recommender systems, such as learner attributes, recommendation methods, evaluation metrics, and the usability tests used by the researchers. It is observed that cognitive aspects of learners like learning style, preferences, knowledge level, etc., are used by most studies than non-cognitive aspects as social tags or trust. In most cases, recommendation engines are a hybrid of collaborative filtering, content-based filtering, ontological approaches, etc. All models were evaluated for the correctness of the prediction done, and a few studies have also done evaluations based on learner satisfaction or usability.

/pdf/a-systematic-literature-review-on-adaptive-content-545swk6vi3.pdf

A systematic literature review on adaptive content recommenders in personalized learning environments from 2015 to 2020

This paper investigates whether the universities’ communication model and the technology acceptance model, which include four factors, namely, academic performance, student satisfaction, effectiveness, and support assessment, simultaneously enhance student satisfaction and improve the teaching method and academic performance level. This paper aims to adapt a model to improve the assessment method and improve the model of student satisfaction. This paper focuses on improving e-learning to activate the feedback of continued intention of using the model that helps to navigate the student understanding level and academic performance immediately. In this paper, surveys were distributed to (295) undergraduates in four universities in Oman to assess their feedback on e-learning. The partial least squares-structural equation model was used to calculate the measurement of all hypotheses proposed. The results of this paper prove that most of the hypotheses are a positive influence on the continuance of intention to use the proposed model.

Continued Intention to Use UCOM: Four Factors for Integrating With a Technology Acceptance Model to Moderate the Satisfaction of Learning

Validation of indicators for implementing an adaptive platform for MOOCs

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Concepcin Bueno

Author Tools

Chat about Author

Papers

Validation of indicators for implementing an adaptive platform for MOOCs