scholarly journals Self-Reported Perceptions of Online Learning and Observed Online Learning Behaviors: To What Extent Are They Consistent?

2021 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Feifei Han
Keyword(s):  
Online Learning ◽  
Hidden Markov ◽  
Learning Outcome ◽  
The Self ◽  
Academic Learning ◽  
Learning Behaviors ◽  
Cluster Membership ◽  
Data Analyses ◽  
Negative Perceptions ◽  
Cross Tabulation

This study investigates to what extent there is an association between students’ self-reported perceptions of online learning and observed online learning behaviors recorded by the learning analytic data. The participants were 319 undergraduates studying an engineering course in an Australian university. Data analyses were conducted using cluster analyses, Hidden Markov Model, one-way ANOVAs, and a cross-tabulation. The relations between students’ self-reported perceptions and their academic learning outcome show that those with positive perceptions tended to have higher scores. The relations between observational online learning behaviors and their academic learning outcome demonstrate that students with most learning sessions achieved more highly. The cross-tabulation finds a significant association between the cluster membership generated by by the self-reported perceptions and observational online learning behaviors. Amongst students who had most study sessions characterized by high percentages of reading and formative states and low percentage of summative states, the proportion of those with positive perceptions (40.2%) was significantly higher than those with negative perceptions (20.0%). Of students who had the least study sessions represented by moderate reading and summative states, and low formative states, the proportion of students with positive perceptions (3.0%) was significantly lower than the proportion of students having negative perceptions (8.7%).

Support for Study: Online Educational Environments and the Rights to Education

2008 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Lin ◽  
Karen Swan
Keyword(s):  
Online Learning ◽  
Conceptual Framework ◽  
Collaborative Inquiry ◽  
Expert Knowledge ◽  
The Self ◽  
Open Educational Resource ◽  
Educational Resource ◽  
Online Learners ◽  
Educational Environments ◽  
Independent Inquiry

This paper uses an online learning conceptual framework to examine the “rights to education” that the current online educational environments could provide. The conceptual framework is composed of three inquiries or three spaces for inquiries, namely, independent inquiry, collaborative inquiry, and formative inquiry towards expert knowledge [42] that online learners pursue and undertake in the process of their learning. Our examinations reveal that most online open educational resource environments (OERs) can incorporate more Web2.0 or Web3.0 technologies so as to provide the self-directed learners, who are the main audience of OERs, with more opportunities to participate, collaborate, and co-create knowledge, and accordingly, to achieve their full rights to education.

scholarly journals Research on the differences of students’ learning styles and knowledge integration in SPOC learning: a case study of course “Basic Portuguese”

2021 ◽  
Vol 18 (1) ◽  
pp. 12-26
Author(s):  
Jing Hu ◽  
Silva Maria Do Carmo Vieira
Keyword(s):  
Online Learning ◽  
Learning Styles ◽  
Learning Style ◽  
Knowledge Construction ◽  
Knowledge Integration ◽  
Teaching Method ◽  
Integration Theory ◽  
Online Data ◽  
Learning Behaviors ◽  
Learning Platform

Problem and goal. With the advent of the information age, Internet-based online learning has also become one of the learning methods chosen by many learners. They can use these online learning platforms to complete knowledge construction while learning offline. Methodology. Most studies of learning behaviors focus on the discovery of the best learning model and disregard the possible impact of different learning behaviors on knowledge construction. Therefore, based on the Felder - Silverman learning style model, this article uses the Solomon learning style scale to improve the design of the questionnaire and collect four-dimensional differential learning behaviors data. In order to further understand the influence of learning styles on the effectiveness of online learning, we also use online learning data on the Small Private Online Course platform and general cognitive intelligence knowledge integration theory to clarify the relation between learning modes and individuals differences. Results. This study observes and analyzes the learning behavior data of 46 students of Nankai University in the SPOC learning platform, also analyzes the differences in learning styles and knowledge construction of students in the SPOC environment. Compared with the traditional Basic Portuguese teaching method, the blended teaching model based on the Chaoxing Learning platform has unparalleled advantages. Interactions inside and outside the classroom, improving student participation and promoting teaching diagnosis. Conclusion. Through a comprehensive analysis of questionnaire data and online data, we found that some learning styles have different effects on the effectiveness of online learning, ignoring the individual differences of learners will still cause problems in knowledge construction.

scholarly journals Using Different Assessment Indicators in Supporting Online Learning

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Online Learning ◽  
Statistical Analysis ◽  
Learning Outcomes ◽  
Learning Process ◽  
Learning Outcome ◽  
Learning System ◽  
Difficulty Level ◽  
Learning Methods ◽  
Analysis Algorithm ◽  
Efficient Learning

The assessment outcome for many online learning methods are based on the number of correct answers and than convert it into one final mark or grade. We discovered that when using online learning, we can extract more detail information from the learning process and these information are useful for the assessor to plan an effective and efficient learning model for the learner. Statistical analysis is an important part of an assessment when performing the online learning outcome. The assessment indicators include the difficulty level of the question, time spend in answering and the variation in choosing answer. In this paper we will present the findings of these assessment indicators and how it can improve the way the learner being assessed when using online learning system. We developed a statistical analysis algorithm which can assess the online learning outcomes more effectively using quantifiable measurements. A number of examples of using this statistical analysis algorithm are presented.

Redefining the Proxemics of the Mentorship

2019 ◽  
pp. 81-100
Author(s):  
Christopher S. Schreiner
Keyword(s):  
Michel Foucault ◽  
Role Models ◽  
Critical Consciousness ◽  
Learning Outcome ◽  
The Self ◽  
Critical Study ◽  
Care Of The Self ◽  
Spatial Contiguity ◽  
Safe Spaces ◽  
Traditional Structures

The sociopolitical controversies on campus that have resulted in “safe spaces” have pressured traditional structures based on proxemics, such as the mentorship, to reinvent themselves or disappear. In the chapter, “proximity” itself is defined not in terms of spatial contiguity but as an attentional structure by which the mentee achieves an intimate understanding at a distance of the objective achievements in teaching and writing that distinguish her mentor and other role models and that provoke acts of creative mimesis and exegesis by the mentee. Inspired by the ancient Stoic practice of the “care of the self” as explicated by Michel Foucault, the crux of the redefined mentored relation is not inculcating knowledge but guiding the growth of the mentee's critical consciousness in preparation for a career and a life well-lived, befitting a noble spirit. Since the focus of the redefined mentored relation privileges distance and objective spirit (via the critical study of works) over personal interaction, the scholarly autonomy of the mentee is a noteworthy learning outcome.

Characterizing Online Learners' Time Regulation

2018 ◽  
pp. 1468-1483
Author(s):  
Margarida Romero ◽  
Christophe Gentil
Keyword(s):  
Online Learning ◽  
Online Education ◽  
Case Studies ◽  
Time Factors ◽  
Time Factor ◽  
Academic Learning ◽  
Online Learners ◽  
Virtual Campus ◽  
The University ◽  
Drop Outs

The importance of the time factor in online learning is starting to be recognized as one of the main factors in the learners' achievements and drop outs (Barbera, Gros, & Kirshner, 2012; Park & Choi, 2009; Romero, 2010). Despite the recognition of the time factor importance, there is still the need for theorizing temporality in the context of online education. In this chapter, the authors contribute to the advancement of the evaluation of time factors in online learning by adapting the theoretical framework of the Academic Learning Times (Caldwell, Huitt, & Graeber, 1982; Berliner, 1984) for evaluating the online learners' time regulation. For this purpose, they compare two case studies based on the Academic Learning Times framework. The case studies characterize online learner regulation based on an analysis of online learners at the Universitat Oberta de Catalunya (UOC), Spain, and the initiatives taken by the instructional team of the Virtual Campus at the University of Limoges (CVTIC) to support online learner time regulation on this virtual campus in France. After comparing the two case studies, the chapter provides guidelines for improving online learners' individual and collaborative time regulation and reflects about the need to advance in the theorization of the time factor frameworks in online education.

scholarly journals A review of predictive factors of student success in and satisfaction with online learning

2015 ◽  
Vol 23 ◽  
Author(s):  
Heather Kauffman
Keyword(s):  
Online Learning ◽  
Instructional Design ◽  
Learning Environment ◽  
Learning Outcomes ◽  
Student Performance ◽  
Online Courses ◽  
Learning Technology ◽  
Learner Characteristics ◽  
Course Structure ◽  
Negative Perceptions

Students perceive online courses differently than traditional courses. Negative perceptions can lead to unfavourable learning outcomes including decreased motivation and persistence. Throughout this review, a broad range of factors that affect performance and satisfaction within the online learning environment for adult learners will be examined including learning outcomes, instructional design and learner characteristics, followed by suggestions for further research, and concluding with implications for online learning pertinent to administrators, instructors, course designers and students. Online learning may not be appropriate for every student. Identifying particular characteristics that contribute to online success versus failure may aid in predicting possible learning outcomes and save students from enrolling in online courses if this type of learning environment is not appropriate for them. Furthermore, knowing these learner attributes may assist faculty in designing quality online courses to meet students’ needs. Adequate instructional methods, support, course structure and design can facilitate student performance and satisfaction.Keywords: online learning; learner characteristics; instructional design; online learning outcomes(Published: 27 August 2015)Responsible Editor: Meg O’Reilly, Southern Cross University, AustraliaCitation: Research in Learning Technology 2015, 23: 26507 - http://dx.doi.org/10.3402/rlt.v23.26507

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