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.

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.

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.

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.

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 Self-Regulation Students’ Online Learning Behavior in General Education Courses of University of Phayao

2021 ◽  
Vol 16 (14) ◽  
pp. 269
Author(s):  
Narin Nonthamand ◽  
Narissara Suaklay
Keyword(s):  
Decision Making ◽  
Online Learning ◽  
General Education ◽  
Online Courses ◽  
Self Regulation ◽  
Stepwise Multiple Regression ◽  
Online Course ◽  
Learning Behavior ◽  
General Education Courses ◽  
Education Courses

This research were aimed 1) to survey the self-regulation behavior among of University of Phayao students 2) to survey the online learning behavior among of University of Phayao students and 3) to study factors on self-regulation that has an influence on an online learning. Sample Group con-sisted of 450 students who enroll general education course of an online courses. The research tool was questionnaire forms about self-regulation in an online course and online learning behavior. The statistics were used to an-alyse the data as follows: mean (M), standard deviation (S.D.), and Stepwise Multiple Regression Analysis. The result found that 1) the students’ behavior on self-regulation was mainly on decision making (M = 3.89) 2) the students’ online learning be-havior was mainly on learner aspect (M = 3.88) and 3) the factors that sup-port students’ online learning behavior consisting of self-observation factor, decision making factor and self-regulation factor. The percentage was 39.90, and shown the raw score and standard score was found from this formula online learning behavior = 0.822 + 0.423 (self-reaction) + 0.183 (self-observation) + 0.141 (decision making) Z online learning behavior = 0.377 Z self-reaction + 0.169 Z self-observation + 0.137 Z decision making

scholarly journals Student Initiative Empowers Engagement for Learning Online

2021 ◽  
Vol 25 (3) ◽  
Author(s):  
Houston Heflin ◽  
Suzanne Macaluso
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Student Perceptions ◽  
Online Courses ◽  
Online Course ◽  
Online Learning Environment ◽  
Self Assessment ◽  
Face To Face ◽  
Amount Of Information

Assessing the degree to which students engage and learn from their online courses will be important as online courses are becoming more ubiquitous. This study sought to capture student perceptions of their independence as learners, their level of engagement, their effort exerted, and the amount of information they learned in online courses. The study was conducted over three years with 455 students who completed a self-assessment at the end of an intensive summer online course. Results showed an equal number of students agreeing and disagreeing that online courses help students learn the same amount of information encountered in a face-to-face course. The majority of students reported they were more independent (84.4%), were more engaged (54.5%) and exerted more effort (57.4%), in their online course than a typical face-to-face class. Recommendations are made for faculty creating online courses who have the opportunity to coach students on how to succeed in the online learning environment.

scholarly journals Accountability for Students in K-12 Online Learning: Perspectives from Michigan Stakeholders and Beyond

2016 ◽  
Vol 20 (3) ◽  
Author(s):  
Leanna Archambault ◽  
Kathryn Kennedy ◽  
Joe Freidhoff
Keyword(s):  
Online Learning ◽  
Online Courses ◽  
Research Policy ◽  
Online Course ◽  
State School ◽  
Policy And Practice ◽  
Virtual University ◽  
National Organizations ◽  
Learning Research ◽  
K 12

Policy surrounding K-12 online learning continues to evolve as the field grows exponentially. In Michigan, Section 21f of the State School Aid Act enacted in 2013 strengthened parents’ and students’ ability to request online courses: “A student enrolled in a district in any of grades 6 to 12 is eligible to enroll in an online course as provided for in this section.” The passing of 21f raised concerns around accountability in a choice environment. Examples of such concerns included a pervasive belief about the lack of rigor or quality in online courses, an aversion to another district educating a student for one or two courses yet remaining responsible for that student’s growth, and uncertainty about how mentors and teachers would be evaluated on their online students. Consequently, a legislative directive was issued to the Michigan Virtual Learning Research Institute, the research arm of Michigan Virtual University that centered on accountability. In response to that directive, Michigan stakeholders, as well as experts from other course access states and national organizations, were interviewed to better understand the conversations surrounding accountability in K-12 online learning in Michigan and beyond and to make key recommendations for moving the field forward in an informed way. Data were analyzed using thematic analysis. Implications for research, policy, and practice are shared.

scholarly journals Including Learning Analytics in the Loop of Self-Paced Online Course Learning Design

2020 ◽  
Author(s):  
Hongxin Yan ◽  
Fuhua Lin ◽  
Kinshuk
Keyword(s):  
Online Education ◽  
Learning Analytics ◽  
Course Design ◽  
Online Course ◽  
Full Potential ◽  
Learning Design ◽  
Design Strategies ◽  
Student Modelling ◽  
Tutoring Systems ◽  
Online Educators

AbstractOnline education is growing because of its benefits and advantages that students enjoy. Educational technologies (e.g., learning analytics, student modelling, and intelligent tutoring systems) bring great potential to online education. Many online courses, particularly in self-paced online learning (SPOL), face some inherent barriers such as learning awareness and academic intervention. These barriers can affect the academic performance of online learners. Recently, learning analytics has been shown to have great potential in removing these barriers. However, it is challenging to achieve the full potential of learning analytics with the traditional online course learning design model. Thus, focusing on SPOL, this study proposes that learning analytics should be included in the course learning design loop to ensure data collection and pedagogical connection. We propose a novel learning design-analytics model in which course learning design and learning analytics can support each other to increase learning success. Based on the proposed model, a set of online course design strategies are recommended for online educators who wish to use learning analytics to mitigate the learning barriers in SPOL. These strategies and technologies are inspired by Jim Greer’s work on student modelling. By following these recommended design strategies, a computer science course is used as an example to show our initial practices of including learning analytics in the course learning design loop. Finally, future work on how to develop and evaluate learning analytics enabled learning systems is outlined.

Online Learning Readiness

2016 ◽  
Vol 12 (1) ◽  
pp. 51-62
Author(s):  
Min-Ling Hung
Keyword(s):  
Online Learning ◽  
Survey Data ◽  
Self Efficacy ◽  
Online Courses ◽  
Learner Control ◽  
Learning Motivation ◽  
Online Course ◽  
Motivation For Learning ◽  
Final Exams ◽  
Online Learning Readiness

The purpose of this study was to examine whether online students' course-related readiness would undergo changes between midterm exams and final exams, and which student-readiness factors might predict students' willingness to take an online course again. The analysis used survey data from 217 students enrolled in an online course that was presented three times over three consecutive semesters. The results of this study were as follows: (1) an increase in communication self-efficacy and a decrease in learner control and in motivation for learning from middle of the semester to the end of the semester; (2) communication self-efficacy and learning motivation were statistically significant predictors of the students' willingness to take future online courses.

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