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Educational Assessment, Evaluation, and Research

Education

2019

STEMPS Faculty Publications

Articles 1 - 2 of 2

Full-Text Articles in Education

Factors Contributing To Student Retention In Online Learning And Recommended Strategies For Improvement: A Systematic Literature Review, Pauline S. Muljana, Tian Luo Jan 2019

Factors Contributing To Student Retention In Online Learning And Recommended Strategies For Improvement: A Systematic Literature Review, Pauline S. Muljana, Tian Luo

STEMPS Faculty Publications

Aim/Purpose

This systematic literature review investigates the underlying factors that influence the gap between the popularity of online learning and its completion rate. The review scope within this paper includes an observation of possible causal aspects within the non-ideal completion rates in online learning environments and an identification of recommended strategies to increase retention rates.

Background

While online learning is increasingly popular, and the number of online students is steadily growing, student retention rates are significantly lower than those in the traditional environment. Despite the multitude of studies, many institutions are still searching for solutions for this matter.

Methodology

A …


Setting The Pace: Examining Cognitive Processing In Mooc Discussion Forums With Automatic Text Analysis, Robert L. Moore, Kevin M. Oliver, Chuang Wang Jan 2019

Setting The Pace: Examining Cognitive Processing In Mooc Discussion Forums With Automatic Text Analysis, Robert L. Moore, Kevin M. Oliver, Chuang Wang

STEMPS Faculty Publications

Learning analytics focuses on extracting meaning from large amounts of data. One of the largest datasets in education comes from Massive Open Online Courses (MOOCs) that typically feature enrollments in the tens of thousands. Analyzing MOOC discussion forums presents logistical issues, resulting chiefly from the size of the dataset, which can create challenges for understanding and adequately describing student behaviors. Utilizing automatic text analysis, this study built a hierarchical linear model that examines the influence of the pacing condition of a massive open online course (MOOC), whether it is self-paced or instructor-paced, on the demonstration of cognitive processing in a …