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This study investigated whether clustering can identify different groups of students enrolled in a massive open online course (MOOC). This study applied self-organizing map and hierarchical clustering algorithms to the log files of a physics MOOC capturing how students solved weekly homework and quiz problems to identify clusters of students showing similar problem-solving patterns. The usefulness of the identified clusters was verified by examining various characteristics of students such as number of problems students attempted to solve, weekly and daily problem completion percentages, and whether they earned a course certificate. The findings of this study suggest that the clustering technique utilizing self-organizing map and hierarchical clustering algorithms in tandem can be a useful exploratory data analysis tool that can help MOOC instructors identify similar students based on a large number of variables and examine their characteristics from multiple perspectives. [ABSTRACT FROM AUTHOR]

Compared with classroom learning, online learning requires students to self-regulate their learning processes and to maintain their motivation to achieve their learning goals. This study investigated whether the interventions based on the Attention, Relevance, Confidence, and Satisfaction model and the modified Introducing the new concepts, Metacognitive questioning, Practicing, Reviewing and reducing difficulties, Obtaining mastery, Verification, and Enrichment method can promote students' motivation and use of self-regulated learning (SRL) strategies in a web-based mathematics learning environment. Two-hundred thirty-six Chinese high school students were randomly divided into four groups: motivational design group, SRL intervention group, motivational design and SRL intervention group, and the control group. Questionnaires and tests were administered to measure the changes in motivation, use of SRL strategies, and academic gains before and after the respective interventions. Findings of this study suggest that the knowledge gain of students learning mathematics online can be maximized when they receive instructional assistance in both motivation and use of SRL strategies. [ABSTRACT FROM AUTHOR]

Although there has been a remarkable increase in the supply of domestic golf courses in South Korea, the demand for golf trips is believed to have reached a plateau. In this competitive environment, golf course managers need to examine diverse constraining factors that discourage their customers from visiting the facilities, and learn how those constraints are managed by golf tourists through a variety of strategies. Using a choice modeling, this study provides useful opportunities to better understand golf tourists’ choices made by intricate comparisons between negotiation strategies that help relieve the impact of golfing constraints. The results indicate that levels of perceived importance vary on several constraint attributes when golf tourists make decisions for golf trips. This study also identifies heterogeneous preferences for negotiation strategies between two golf tourist groups segmented based on their golfing experiences. [ABSTRACT FROM AUTHOR]