LIWC analysis shows synchronous messages carry more social and emotional language while asynchronous notes carry more cognitive-processing language¶

Claim · All claims
Evidence · 1 study (3 entries) · associational r2 · q2
Currency · newest study 2012 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Synchronous messages contain a larger proportion of social-process words than asynchronous notes (12.02 vs 8.21 percent). → Murat Oztok 2012 q2 i? Synchronous messages contain more emotional words than asynchronous notes (6.79 vs 4.51 percent). → Murat Oztok 2012 (2) q2 i? Asynchronous notes contain a larger percentage of cognitive-process words than synchronous messages (18.95 vs 16.17 percent). → Murat Oztok 2012 (3)

Evidence¶

Murat Oztok 2012¶

Murat Oztok, Daniel Zingaro, Clare Brett, Jim Hewitt. (2012). Exploring Asynchronous and Synchronous Tool use in Online Courses. Preprint submitted to Computers & Education. https://doi.org/10.1016/j.compedu.2012.08.007

q2 · i? · associational · r2

LIWC dictionary analysis of transcripts from the nine dual-mode online courses, 190 message-writing students. The quote reports "12.02 percent compared to 8 .21 percent" social words with t(189) = 9.61, p = 0.

"Using the social dictionary, we found that messages contained a larger proportion of social words than did notes (12.02 percent compared to 8 .21 percent; t(189) = 9.61,p = 0)."

Murat Oztok 2012 (2)¶

Murat Oztok, Daniel Zingaro, Clare Brett, Jim Hewitt. (2012). Exploring Asynchronous and Synchronous Tool use in Online Courses. Preprint submitted to Computers & Education. https://doi.org/10.1016/j.compedu.2012.08.007

q2 · i? · associational · r2

Same LIWC analysis using the affective-processes dictionary on the same dataset. The quote reports "6.79 percent compared to 4 .51 percent" emotional words with t(189) = 3.43, p = .0008.

"Similarly, compared to notes, messages contained more emotional words (6.79 percent compared to 4 .51 percent; t(189) = 3.43;p = .0008)."

Murat Oztok 2012 (3)¶

Murat Oztok, Daniel Zingaro, Clare Brett, Jim Hewitt. (2012). Exploring Asynchronous and Synchronous Tool use in Online Courses. Preprint submitted to Computers & Education. https://doi.org/10.1016/j.compedu.2012.08.007

q2 · i? · associational · r2

Same LIWC analysis using the cognitive-processes dictionary on the same nine-course dataset. The quote reports "18.95 percent compared to 16.17 percent" cognitive words with t(189) = 7.52, p = 0.

"By contrast, when using the dictionary of cognitive words, we found that notes contained a larger percentage of words indicating cognitive processing than messages (18.95 percent compared to 16.17 percent; t(189) = 7.52,p = 0)."

Discussion¶

Related Claims¶

• Forum discussion contains more social and regulative comments and longer messages; anchored discussion is briefer with more messages — reports the opposite
• Regulatory sequencing in synchronous CSCL: cognitive interactions initiate cycles, co-regulation iterates with task execution, and SSRL follows socio-emotional interactions — related
• Synchronous private messages are shorter, easier to read, and use fewer academic words than asynchronous notes in dual-mode online courses — related
• Teacher-student online interaction pattern significantly moderates blended instruction effects, with synchronous + asynchronous interaction largest (SMD = 1.189) and absence of interaction smallest (SMD = 0.130) — related
• Proposed course provides highest human interaction among compared courses — related