mooceology - honing in on social learning in mooc forums: examining critical network definition...

Honing in on Social Learning in MOOC Forums: Examining Critical Network Definition Decisions

Alyssa Wise, Yi Cui, Wan Qi JinLAK’17, March 2017, Vancouver, CANADA

Investigation of the interaction practices in large-scale learning environments based on analysis of the artifacts left behind by learners’ and instructors’ activity.

MOOCEOLOGY

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QUESTIONS DATA METHODS RESULTS CONCLUSION

RQ1: What effects do different tie definitions have on network characteristics?

RQ2: In what ways do unpartitioned, content-related, and non-content social networks show distinct characteristics?

RQ3: What differences in the discussion interactions may account for the distinctions between networks?

Research Questions

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Learning Context & Data • A MOOC on statistics in medicine

• 3-level posting structure

• Forums facilitated by 2 instructional team members

• 567 users

• 817 threads containing 3124 posts 4


Content-based Partitioning• Content-related = Q&As/comments related to the course subject • Non-Content = Others (logistical & technical Q&As, socilizing) • Method: Dynamic Interrelated Post and Thread Categorization

(Cui, Jin, & Wise, in press), est. accuracy = .88

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Non-content

Content-re-lated

Threads

468 threads

349 threadsContent-related activities

17831%

Both15728%

Non-content activities 23241%

PARTICIPANTS


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RQ1: Tie Definition Effects


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Tie Definition Effects - Resulting Network Properties

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Content-related network(# of nodes = 335, # of edges = 848)

Non-content network(# of nodes = 389, # of edges = 724)

RQ2 & 3: Content vs Non-Content Networks

Content-related Non-content


CL1 NL1 NL20123456789

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Avg node degree

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Learner Modules

CL = Content-related Learner Module NL = Non-content learner module

CL1(# of nodes = 23, # of edges =57)

NL1(# of nodes = 62, # of edges =71)

NL1(# of nodes = 23, # of edges = 28)


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Content vs Non-Content Discussions1. Thread Characteristics

Content-related Module 1

Non-content Module 1

Non-content Module 2

# of contributing threads 30 2 11

Avg # of posts per participant in thread 2.41 (1.62) 1.13 (0.07) 1.42 (0.53)

Avg # of posts per thread (SD) 13.4 (14.85) 6, 93 6 (5.75)

2. Activity characteristics: content-related activities involved more• complicated topics• interaction techniques • social presence cues


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U225: Congrats [u10]! Yes, it has been hard, but fun, and we learned an awful lot, right?U110: Great! Everyone it was a pleasure to work with you. Thank you….U10: YES [u225]! And [u110] - the test was scary - I thought of my discussion board friends often!!U216: Thanks, thanks so much to [u10], [u152], [u110], [u225] and everybody who helped us to understand this beautiful course! And in my case also for writing many posts, I see I have improved my English skills and my statistics vocabulary!!!U225: [u10], [u216], [u152], [u110], [u515] and everyone, your discussions helped me so much. I was always a few days behind you in homework - glad I was able to catch up in the last weeks and participate a little bit….

Content-related learner module 1

Examining Learner Interaction

U225: [u10], [u216], [u152], [u110], [u515] and everyone, your discussions helped me so much. I was always a few days behind you in homework - glad I was able to catch up in the last weeks and participate a little bit….

U10: YES [U225]! And [u110] - the test was scary - I thought of my discussion board friends often!!


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CI1 CI2 NI1 NI2

# of nodes (% in network) 184 (54.93%) 75 (22.39%) 168 (43.19%) 47 (12.08%)

# of edges (% in network) 400 (47.17%) 105 (12.38%) 315 (43.51%) 55 (7.6%)

Avg node degree (SD) 4.35 (11.06) 2.8 (7.56) 3.75 (11.18) 2.34 (6.03)

Avg edge weight (SD) 2.23 (3.21) 1.83 (1.72) 2.11 (2.48) 1.20 (0.44)

Instructor Modules

CI = Content-related instructor module NI = Non-content instructor module

CI1 CI2 NI1 NI2


U1 • Responses at all levels• Coaching and supporting • Social presence cues

U417• Responses to thread starters• Straight forward answers • Little social presence

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Comparing Intervention Approaches


“Think about it again using the hint and let me know if you have any other questions.”

“That is correct - Nice! So how would you use this to solve the question?”

“A bell shape is not necessary. You could have a 'bimodal' distribution where the two groups do not follow a bell shape.”

Conclusions• Tie definition affects network and interpretation.

• Content-related and non-content networks had distinct characteristics.

• Content-related discussions led to wider and deeper learner connection; instructor’s intervention approach may also affect it.

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