Using Learning Analytics to Enhance Student Learning in Online Courses Based on Quality Matters Standards

2016 ◽  
Vol 45 (2) ◽  
pp. 165-187 ◽  
Author(s):  
Florence Martin ◽  
Abdou Ndoye ◽  
Patricia Wilkins
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Online Course ◽  
Design Quality ◽  
Descriptive Data ◽  
Quality Matters ◽  
Frequency Of Use ◽  
And Performance ◽  
Enhance Student Learning

Quality Matters is recognized as a rigorous set of standards that guide the designer or instructor to design quality online courses. We explore how Quality Matters standards guide the identification and analysis of learning analytics data to monitor and improve online learning. Descriptive data were collected for frequency of use, time spent, and performance and analyzed to identify patterns and trends on how students interact with online course components based on the Quality Matters standards. Major findings of this article provide a framework and guidance for instructors on how data might be collected and analyzed to improve online learning effectiveness.

Learning Analytics Considered Harmful

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus
Keyword(s):  
Big Data ◽  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Research Community ◽  
Current Status ◽  
Online Course ◽  
Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

scholarly journals Understanding Learner Behaviour in Online Courses through Learning Analytics

2021 ◽  
pp. 381-390
Author(s):  
D. Thammi Raju ◽  
G. R. K. Murthy ◽  
S. B. Khade ◽  
B. Padmaja ◽  
B. S. Yashavanth ◽  
...  
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Learning Experience ◽  
Training Needs ◽  
Online Course ◽  
Quality Of Education ◽  
Time Data

Building an effective online course requires an understanding of learning analytics. The study assumes significance in the COVID 19 pandemic situation as there is a sudden surge in online courses. Analysis of the online course using the data generated from the Moodle Learning Management System (LMS), Google Forms and Google Analytics was carried out to understand the tenants of an effective online course. About 515 learners participated in the initial pre-training needs & expectations’ survey and 472 learners gave feedback at the end, apart from the real-time data generated from LMS and Google Analytics during the course period. This case study analysed online learning behaviour and the supporting learning environment and suggest critical factors to be at the centre stage in the design and development of online courses; leads to the improved online learning experience and thus the quality of education. User needs, quality of resources and effectiveness of online courses are equally important in taking further online courses.

scholarly journals Applying the Matrix Model in an English for Presentation Online Class during COVID-19 Pandemic: A Case Study of an Undergraduate Class in Thailand

2021 ◽  
Vol 14 (9) ◽  
pp. 12
Author(s):  
Prapaporn Sompakdee ◽  
Wichuta Chompurach ◽  
Werachai Thanamaimas ◽  
Siraprapa Kotmungkun
Keyword(s):  
Online Learning ◽  
Matrix Model ◽  
Online Courses ◽  
Private University ◽  
Online Course ◽  
The Matrix ◽  
Online Course Development ◽  
Data Collections ◽  
Class Presentation ◽  
Academic Year

During the COVID-19 pandemic, online learning was an important topic for scholars. A private university in Khon Kaen Province, Thailand followed a policy to create online courses for every subject to ensure that education could proceed effectively. To correspond with the policy, the Matrix Model was integrated with the online course development of an English for Presentation class at this private university. The Matrix Model is also known as SAMR which refers to Substitution, Augmentation, Modification, and Redefinition. The online course was presented in the third semester of the academic year of 2019 with 77 participants who volunteered to participate in this course. The research instruments used in this study were observation, surveying, and interview. The data collections were done at the beginning, during, and after the course to provide a comprehensive study of online learning. The data revealed both positive opinions and obstacles associated with this online learning. The results of using the SAMR model in this study do provide benefits to students and educators and show that 84% of the participants prefer online presentation over in-class presentation.

scholarly journals Using Learning Analytics to Assess Student Learning in Online Courses

2016 ◽  
Vol 13 (3) ◽  
pp. 110-130 ◽  
Author(s):  
Florence Martin ◽  
◽  
Abdou Ndoye ◽  
Keyword(s):  
Learning Analytics ◽  
Data Analytics ◽  
Qualitative Data ◽  
Online Courses ◽  
Instructional Designers ◽  
Data Sets ◽  
Online Assessments ◽  
Visualization Tools ◽  
And Performance ◽  
Analyze Data

Learning analytics can be used to enhance student engagement and performance in online courses. Using learning analytics, instructors can collect and analyze data about students and improve the design and delivery of instruction to make it more meaningful for them. In this paper, the authors review different categories of online assessments and identify data sets that can be collected and analyzed for each of them. Two different data analytics and visualization tools were used: Tableau for quantitative data and Many Eyes for qualitative data. This paper has implications for instructors, instructional designers, administrators, and educational researchers who use online assessments.

scholarly journals 9. Quality Matters: A Faculty-Centred Program to Assure Quality in Online Course Design

2011 ◽  
Vol 3 ◽  
pp. 49 ◽  
Author(s):  
Kay Shattuck
Keyword(s):  
Review Process ◽  
Course Design ◽  
Online Courses ◽  
Peer Review Process ◽  
Research Literature ◽  
Quality Assurance Program ◽  
Online Course ◽  
Design Standards ◽  
Online Course Design ◽  
Quality Matters

One of the dilemmas faced by today’s faculty is assuring quality in online courses. As one solution to that dilemma, Quality Matters (QM), a program of MarylandOnline, built a rubric of design standards informed by existing research literature and best practices. The rubric was implemented within a faculty-centred, peer review process in which colleagues share their expertise to facilitate course design improvements and to achieve an established level of quality in online course design. This article will describe the basic tenets and processes of QM as an inter-institutional quality assurance program for online learning.

Using Gagné's Events of Instruction to Analyze Online Course Quality

2011 ◽  
pp. 2231-2238 ◽  
Author(s):  
Marc R. Robinson
Keyword(s):  
Instructional Design ◽  
Online Education ◽  
Learning Community ◽  
Student Perceptions ◽  
Course Design ◽  
Online Courses ◽  
Online Course ◽  
Design Quality ◽  
Course Quality ◽  
Events Of Instruction

Student perceptions of online courses are likely influenced by two overarching aspects of quality: instructor quality and course design quality (Ortiz-Rodriguez, Telg, Irani, Roberts & Rhoades, 2005). Both of these forces in online education may be analyzed using a well-known model of instructional design - Gagnés instructional design and cognition theory, the centerpiece of which are the nine events of instruction (Gagné, Wager, Golas, & Keller, 2004). Multiple studies positively correlate learner attitudes and perceptions of the online course to instructor quality. Early studies evaluating instructor quality attempted to correlate instructor quality with the attitude and perception of the learner, but not directly to learner success or course design quality. Researchers of online courses, such as Palloff & Pratt (2003), discussed the role of the instructor in depth while neglecting the roles of the learner, the institution, and course design. The main focus remained instructor-centered, and highlighted key instructor tasks such as understanding the virtual learner in terms of roles the learner plays, fostering team roles for the learner, designing an effective course orientation, and identifying potential legal issues the instructor might face (Palloff & Pratt, 2002, p. 16). A distant secondary focus was on effective course design. This highlighted instructor tasks in building an effective online learning community without highlighting the roles effective communication tools would play.

Most courses are not born digital

2014 ◽  
Vol 31 (4) ◽  
pp. 217-229 ◽  
Author(s):  
Evangeline Marlos Varonis
Keyword(s):  
Online Learning ◽  
Peer Review ◽  
Review Process ◽  
Course Design ◽  
Online Courses ◽  
Peer Review Process ◽  
Online Course ◽  
Shared Services ◽  
Online Course Design ◽  
Content Type

Purpose – The purpose of this paper is to discuss benefits of and barriers to online learning and describe utilization of the Quality Matters (QM) peer review process as a method to assure the quality of online courses. It outlines the QM higher education rubric, explains how the collaborative QM peer review process facilitates online course design and certification, reports on the development of a statewide consortium in Ohio, and explores future directions in online courses. Design/methodology/approach – This paper offers a brief historical review of the incorporation of technology into teaching and learning. It describes attitudes toward online learning and the creation of the non-profit QM program as a vehicle for improving online course design. It summarizes the eight standards of the QM rubric, describes the QM peer review process, and discusses the implementation of the Ohio QM Consortium (OQMC) as a shared services model. Findings – Given existing barriers to online learning, the QM program can improve learning outcomes by offering best practices in online course design, validating the quality of online courses, encouraging faculty buy-in through a focus on design rather than content, and facilitating degree completion through recognition of quality courses. Practical implications – Institutions that seek to validate online course quality in a cost-effective manner can explore a shared services model such as that developed by the OQMC. Originality/value – This paper introduces to an international audience a program and process, widely implemented in the USA, which encourages inter-institutional cooperation and promotes a supportive culture among online educators.

Effects of Chronotypes on Students’ Choice, Participation, and Performance in Online Learning

2017 ◽  
Vol 55 (8) ◽  
pp. 1069-1087 ◽  
Author(s):  
Yi Luo ◽  
Rui Pan ◽  
Jea H. Choi ◽  
Johannes Strobel
Keyword(s):  
Online Learning ◽  
Significant Relationship ◽  
Exploratory Study ◽  
Online Courses ◽  
Biological Clock ◽  
Discussion Board ◽  
Learning Time ◽  
Course Grades ◽  
And Performance ◽  
Blackboard Learn

Introducing a new theoretical framework of chronotypes (inner biological clock), this article presents a study examining students’ choices, participation, and performance in two discussion-heavy online history courses. The study comprised two major parts: a repetition study and an exploratory study. The survey adopted in the repetition study mainly contained questions asking about participants’ preferred time of conducting online learning (a multiple-choice question), why participants choose online learning (7-point Likert scale questions), and questions to identify their chronotypes from the Munich ChronoType Questionnaire. The repetition study confirms the statistically significant relationship among the three factors for choosing online learning: students’ perceived level of control, independence, and satisfaction. A significant correlation is also identified between students’ chronotypes and their preferred online learning time. The second part of the research explored the level of participation and performance of students having different chronotypes. The students’ participation data collected were the timestamps recording each participant’s hits on the Blackboard Learn courses. The performance data were students’ final course grades, discussion board grades, and group wiki grades. The results indicate there is a statistically significant relationship between students’ chronotypes and the time of their activity in online courses. The overall level of participation affects students’ performance in online learning—students who are more active in the learning management system are likely to have higher final course grades. Implications and limitations of the study are discussed.

scholarly journals Strategies for innovative teaching and learning Part 2: How to deliver a distance education online course

2021 ◽  
Vol 11 (9) ◽  
pp. 39
Author(s):  
Constance E. McIntosh ◽  
Diana Bantz ◽  
Cynthia M. Thomas
Keyword(s):  
Distance Education ◽  
Online Learning ◽  
Distance Learning ◽  
Teaching And Learning ◽  
Online Courses ◽  
Online Course ◽  
Innovative Teaching ◽  
Advantages And Disadvantages ◽  
Learning Platform ◽  
History Of

The second article in a three-part series discusses how to deliver a distance education online course by i) assuring understanding of the learning platform, ii) developing a course model, iii) creating individual assignment rubrics for courses, iv) requiring active participation from both instructor and students, and v) setting-up quality communication. This paper is a continuation of the first paper whereby the history of distance learning, the positives and negatives of online learning, advantages and disadvantages of online learning, and the initial considerations for establishing online courses.

scholarly journals Visualizing Student Behavior and Performance in an Online Course

2021 ◽  
Author(s):  
Michael J Parker
Keyword(s):  
Online Learning ◽  
Student Behavior ◽  
Online Course ◽  
Course Structure ◽  
Course Material ◽  
Potential Benefits ◽  
And Performance ◽  
The Impact ◽  
The Relationship

Online learning has been an area of tremendous growth in recent years [1], further accelerated by necessity during the coronavirus pandemic [2]. Without the feedback provided by synchronous sessions, however, instructors may lack ongoing insight into students’ progress and performance in fully asynchronous online offerings. Providing greater visibility into students’ online learning behavior has several potential benefits: 1) teachers who seek to provide live sessions that depend on knowledge from asynchronous resources will have a better gauge of students’ preparation; 2) enhanced understanding of the relationship between student pacing and performance can help teachers and researchers characterize the impact of timely engagement with online course material; 3) providing a means of monitoring the effect of changes in course structure or incentives may guide course designers/planners in continuous improvement; and 4) visualizations that illustrate the relationship between students’ course progress and performance have the promise of allowing teachers to take steps early to positively affect students’ outcomes. In this visual case study, visualizations are provided for exploration of the relationship between student progress and performance in an online medicine-related course.

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