Distance learning course formats can alter modes of information exchange and interpersonal interaction relative to traditional course formats. This study aims to determine the effect of a distance course format on the knowledge acquisition (cognitive learning) and satisfaction (affective learning) of students, we investigated student learning responses and social presence during a graduate?level engineering course taught via traditional (i.e., professor present in the classroom) and synchronous distance?learning formats. Direct quantification of participation, academic performance assessment based on homework and exam scores, and survey?based assessments of student perceptions of the course were collected. Based on these data, cognitive and affective learning responses to different technological and interaction?based aspects of the course were determined for each course format. We show that while affective learning decreased for students in the distance format course relative to the traditional format, cognitive learning was comparable. Our results suggest that loss of satellite connection and audio losses had a stronger negative effect on student perceptions than video disturbances, and that participation was the most important factor influencing affective learning.
While our findings do not suggest that cognitive learning is strongly affected by social presence, implementing strategies to enhance social presence may improve the overall learning experience and make distance learning more enjoyable for students.
Distance learning, Participation, Social presence
This study compared knowledge acquisition (cognitive learning) and student satisfaction (affective learning) in a traditional and an online graduate engineering course. To assess knowledge acquisition, student grades and perceptions were examined. Satisfaction was lower in online courses but knowledge gained was the same. Twitter account and interacted with students in educationally relevant ways. After 14 weeks, the experimental group had a higher increase in student engagement (as measured by 19 questions from the NSSE) and higher GPAs. Prior to the experiment, no difference in engagement or GPAs existed between the two groups. The authors also present a qualitative analysis of three types of tweets: a book discussion, panel discussion, and study group formation. The authors suggest that further research is needed to determine how much of the effects can be linked to Twitter, and how much can be linked to the “Web 2.0 mentality” of the faculty members that resulted in increased faculty-student interaction. Additionally, this experiment must be replicated on a larger, more diverse population.
Using the NESSE engagement scale in student surveys, the authors found that there was a positive effect on students who used Twitter in educationally relevant ways. It also had a positive effect on grades. An analysis of student tweets found that they were actively engaged in course content and thoughtful conversations that went on for hours.
Mackey, K. R. M., & Freyberg, D. L. (2010). The effect of social presence on affective and cognitive learning in an international engineering course taught via distance learning. Journal of Engineering Education, 99, 23-34.
|Links to Article||https://scholar.google.com/scholar?hl=en&as_sdt=0%2C50&q=Mackey%2C+K.+R.+M.%2C+%26+Freyberg%2C+D.+L.+%282010%29.+The+effect+of+social+presence+on+affective+and+cognitive+learning+in+an+international+engineering+course+taught+via+distance+learning.+Journal+of+Engineering+Education%2C+99%2C+23-34.&btnG=
|Publication Type||Journal Article|
|In Publication||Journal of Engineering Education|
|Type of Research||Quantitative|
|Research Design||Survey research (qualitative or quantitative)|
|Intervention/Areas of Study||Digital lecture, Learning community, Multimedia, Personalized learning|
|Level of Analysis||Student-level|
|Specific Populations Examined||Graduates|
|Specific Institutional Characteristics of Interest||4-year Institution, Masters-granting|
|Specific Course or Program Characteristics||STEM|
|Outcome Variables of Interest||Academic achievement or performance, including assessment scores and course grades, Learning effectiveness|
|Student Sample Size||100-199|