Do Online Courses Provide an Equal Educational Value Compared to In-Person Classroom Teaching? Evidence from US Survey Data Using Quantile Regression

Education has traditionally been classroom-oriented with a gradual growth of online courses in recent times. However, the outbreak of the COVID-19 pandemic has dramatically accelerated the shift to online classes. Associated with this learning format is the question: what do people think about the educational value of an online course compared to a course taken in-person in a classroom? We address this question and present a Bayesian quantile analysis of public opinion using a nationally representative survey data from the United States. We find that previous participation in online courses and full-time employment status favor the educational value of online courses. We also find that the older demographic and females have a greater propensity for online education. In contrast, highly educated individuals have a lower willingness towards online education vis-à-vis traditional classes. Regional variations in the propensity to value online classes also exist. Besides, covariate effects show heterogeneity across quantiles which cannot be captured using probit or logit models.

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Tweeting Continuing Education

International Journal of Strategic Decision Sciences ◽

10.4018/ijsds.2018010106 ◽

2018 ◽

Vol 9 (1) ◽

pp. 79-101

Author(s):

Ritanjali Panigrahi ◽

Praveen Ranjan Srivastava

Keyword(s):

Social Media ◽

Continuing Education ◽

Online Courses ◽

Massive Open Online Courses ◽

Classroom Teaching ◽

Massive Open Online ◽

Twitter Data ◽

Social Media Tools ◽

The Government ◽

Conventional Classroom

The rapid growth of technology has transformed education from conventional classroom teaching to learner centred, flexible learning anytime anywhere resulting in the popularity of Massive Open Online Courses (MOOCs). It is evident that many MOOCs have adopted social media tools to engage their learners through information sharing, participation, and collaboration to create and consume information. In addition to this, social media is the best place to understand crowd sentiments considering the massive amount of data being generated. This study through text mining of MOOC providers related Twitter data discovers the sentiments of users towards MOOCs, association rules, and the engagement of MOOC providers in Twitter. This article also analyses the traits of the influencers in seven MOOC providers and discovers that the influencers are popular users with higher numbers of followers count. The implications are discussed for MOOC industry, academic institutions, and the government.

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Opinion of Computer Science Instructors and Students on MOOCs in an Indian University

Journal of Educational Technology Systems ◽

10.1177/0047239518797085 ◽

2018 ◽

Vol 47 (2) ◽

pp. 205-212 ◽

Cited By ~ 8

Author(s):

Pushp Sra ◽

Pinaki Chakraborty

Keyword(s):

Artificial Intelligence ◽

Computer Science ◽

Undergraduate Students ◽

Online Courses ◽

Massive Open Online Courses ◽

Computer Networking ◽

Classroom Teaching ◽

Massive Open Online ◽

Effective Form ◽

Science Instructors

Massive open online courses (MOOCs) have lately emerged as an effective form of distance education. Computer science is one of those disciplines in which MOOCs are quite common. We conducted a survey to know the opinion of computer science instructors and undergraduate students on MOOCs in an Indian university in March 2018. Of the 26 instructors and 273 students who participated, 73% instructors and 87% students reported to have attended MOOCs. We found that 50% instructors and 72% students considered MOOCs to be a more comprehensive source of knowledge and 54% instructors and 76% students felt that MOOCs let students learn faster when compared to courses taught in a classroom. Moreover, 58% instructors believed that the courses they teach in classrooms can also be taught effectively through MOOCs. The instructors and students appreciated several aspects of MOOCs. However, the students had an opinion that MOOCs can augment classroom teaching but cannot replace it. MOOCs on computer programming (22%), artificial intelligence (9%), and computer networking (8%) were found to be particularly popular among the students.

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Online Learning Readiness

International Journal of Technology and Human Interaction ◽

10.4018/ijthi.2016010104 ◽

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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