This is a presentation at ASEE2012, San Antonio, Texas. Mining Twitter data to understand engineering students learning experiences. This presentation contains the qualitative research part. An updated version of this project with large-scale data mining (using classification and detection algorithm to identify potentially at-risk students) is published in this paper. http://web.ics.purdue.edu/~chen654/pub/XinChen_etal_IEEETrans_tlt-cs_Mining_Twitter.pdf

1. Exploring Engineering Students’ College Experiences
Using Social Media Monitoring Tool Radian6
Xin Chen, Mihaela Vorvoreanu Ph.D, Krishna Madhavan Ph.D
Purdue University
{chen654, mihaela, cm}@purdue.edu

2. The story begins with:

3. The story begins with:
Social Media Proliferation

4. The story begins with:
Social Media Proliferation

5. The story begins with:
Social Media Proliferation

6. The story begins with:
Social Media Proliferation
Data Deluge
Image: http://www.psfk.com/2011/01/building-digital-libraries-to-contain-the-data-deluge.html

7. What insights do we gain from user generated data?

8. What insights do we gain from user generated data?
Brand Monitoring

9. What insights do we gain from user generated data?
Brand Monitoring

10. What insights do we gain from user generated data?
Brand Monitoring

11. What insights do we gain from user generated data?
Brand Monitoring

12. What insights do we gain from user generated data?
Brand Monitoring

13. What insights do we gain from user generated data?
Event Monitoring
Brand Monitoring

14. What insights do we gain from user generated data?
Event Monitoring
Brand Monitoring

15. What insights do we gain from user generated data?
Event Monitoring
Brand Monitoring
Disaster Responses

16. What insights do we gain from user generated data?
Disaster Responses
Event Monitoring
Brand Monitoring

17. What insights do we gain from user generated data?
Disaster Responses
Event Monitoring
Brand Monitoring
Network Analysis

18. How does higher education use social media data?

19. How does higher education use social media data?
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

20. How does higher education use social media data?
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

21. How does higher education use social media data?
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

22. How does higher education use social media data?
Mostly Number Counting, No Content Analysis
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

23. How does higher education use social media data?
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

24. How does higher education use social media data?
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

25. How does higher education use social media data?
Mostly for Marketing, Not Directly Related to Current Students
The State of Web and Social Media Analytics in Higher Ed, Survey by Higher Ed Experts, July 2011

26. Methods
Strategy
Collect web content relevant to
engineering students to understand
their college experiences

27. Methods
Strategy
Collect web content relevant to
engineering students to understand
their college experiences
Challenge
Relevant vocabulary is undefined; time
span is undefined.

28. Methods

29. Methods
Iterative process of defining keywords
combination for data retrieval using Radian6

30. Methods
Iterative process of defining keywords
combination for data retrieval using Radian6
Oct. 31st -- Nov. 30th, 2011
Keywords combination: 116 tweets
#engineeringProblems: 667 tweets

31. Methods
Iterative process of defining keywords
combination for data retrieval using Radian6
Oct. 31st -- Nov. 30th, 2011
Keywords combination: 116 tweets
#engineeringProblems: 667 tweets
Two stages of content analysis

32. Results
1
Sacrifice and Negative Feelings
2
Issues with Classes, Professors, Homework, and Exams
3
Gender and Other Minorities
4
Engineer Stereotypes and Identity Formation

33. The results: 4 major themes
1
Sacrifice and Negative Feelings

34. The results: 4 major themes
1
Sacrifice and Negative Feelings
“Which one of does not belong: coloring eggs, hunting for
eggs, new dog, time with my mommy, Easter feast, studying?”

35. The results: 4 major themes
1
Sacrifice and Negative Feelings
“Which one of does not belong: coloring eggs, hunting for
eggs, new dog, time with my mommy, Easter feast, studying?”
“I’ve got 482 followers! That’s 480 more friends than I have
in real life! Thanks for being there for me mom and dad!”

36. The results: 4 major themes
1
Sacrifice and Negative Feelings
“Which one of does not belong: coloring eggs, hunting for
eggs, new dog, time with my mommy, Easter feast, studying?”
“I’ve got 482 followers! That’s 480 more friends than I have
in real life! Thanks for being there for me mom and dad!”
“Is it bad that before I started studying for my tests today
that I considered throwing myself in front of a moving car??”

37. The results: 4 major themes
2
Issues with Classes, Professors, Homework, and Exams

38. The results: 4 major themes
2
Issues with Classes, Professors, Homework, and Exams
“Learning more from a hick on YouTube than from my
professor.”

39. The results: 4 major themes
2
Issues with Classes, Professors, Homework, and Exams
“Learning more from a hick on YouTube than from my
professor.”
“I’ve never been so happy to make a 50 on a test! Beat the
class average by over 20 points.”

40. The results: 4 major themes
2
Issues with Classes, Professors, Homework, and Exams
“Learning more from a hick on YouTube than from my
professor.”
“I’ve never been so happy to make a 50 on a test! Beat the
class average by over 20 points.”
“Would it kill him to just put one problem on the test
that we’ve actually seen before?”

41. The results: 4 major themes
3
Gender and Other Minorities Issues

42. The results: 4 major themes
3
Gender and Other Minorities Issues
“Finally talked to a girl today!!! ...It was Siri.”

43. The results: 4 major themes
3
Gender and Other Minorities Issues
“Finally talked to a girl today!!! ...It was Siri.”
“Trying to find a girls bathroom in an engineering building”

44. The results: 4 major themes
3
Gender and Other Minorities Issues
“Finally talked to a girl today!!! ...It was Siri.”
“Trying to find a girls bathroom in an engineering building”
“85 kids leaving the classroom before mine…of those 85
four are girls. Engineers math class #Stereotypical”

45. The results: 4 major themes
3
Gender and Other Minorities Issues
“Finally talked to a girl today!!! ...It was Siri.”
“Trying to find a girls bathroom in an engineering building”
“85 kids leaving the classroom before mine…of those 85
four are girls. Engineers math class #Stereotypical”
“I get a B- on my public speech because I talked about
The National Society Of Black Engineers.”

46. The results: 4 major themes
4
Engineer Stereotypes and Identity Formation

47. The results: 4 major themes
4
Engineer Stereotypes and Identity Formation
“I am f***ing studying engineering but who am I really? A
nerd!!! Dawg a nerd! No one looks at engineers as special
alight! Read that!”

48. The results: 4 major themes
4
Engineer Stereotypes and Identity Formation
“I am f***ing studying engineering but who am I really? A
nerd!!! Dawg a nerd! No one looks at engineers as special
alight! Read that!”
“Professor just called us nerds. Every room I go in it smells
like nerd...strong.”

49. The results: 4 major themes
4
Engineer Stereotypes and Identity Formation
“I am f***ing studying engineering but who am I really? A
nerd!!! Dawg a nerd! No one looks at engineers as special
alight! Read that!”
“Professor just called us nerds. Every room I go in it smells
like nerd...strong.”
“I hate having class in the Engineering building. Engineers
don’t shower”

50. Implications and Future works

51. Implications and Future works
1
Research and Policy Implications

52. Implications and Future works
1
Research and Policy Implications
2
Social Support, Community Building

53. Implications and Future works
1
Research and Policy Implications
2
Social Support, Community Building
3
Social Media Analytics Tool for Education

54. Are these Twitter users building a community?
Partial #engineeringProblems Network based
on Mentions, Replies, and Follows

55. Questions ?
Xin Chen, Mihaela Vorvoreanu Ph.D, Krishna Madhavan Ph.D
Purdue University
{chen654, mihaela, cm}@purdue.edu