Title: Social Epistemic Cognition in Engineering Learning: Theory, Pedagogy, and Analytics Speaker: Prof. Rosanna Yuen-Yan Chan, Member-at-Large, Board of Governors, IEEE Education Society Department of Information Engineering, The Chinese University of Hong Kong Time: 14:15-15:15, 9 June 2018 (Saturday) Venue: Rayson Huang Theatre, The University of Hong Kong Sub-theme: Learning design and learning analytics Chair: Dr. Gary Wong, Faculty of Education, The University of Hong Kong http://citers2018.cite.hku.hk/program-highlights/keynote-chan/

1. CITE Research Symposium 2018
Keynote
Social Epistemic Cognition in Engineering
Learning: Theory, Pedagogy, and Analytics
Rosanna Yuen-Yan Chan
Department of Information Engineering
The Chinese University of Hong Kong
9 June 2018
Rayson Huang Theatre, HKU

2. Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 2
Social Epistemic Cognition
Theory
Learning Analytics
Learning Design
(Implementation Case in
Engineering Education)
Agenda of My Talk

3. Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 3

4. Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 4

5. Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 5

6. Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 6

7. Engineering Education in the 21st
Century
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 7
(Image source: Computer Business Review)

8. Engineering Education in the
21st Century
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 8
(Image source: The United Nations)

9. • Engineering education communities demand for
research results that can inform about the
collection and analysis of scientific evidence in
engineering students’ learning.
9Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018
Engineering Education in the
21st Century

10. Engineering Epistemology
• Engineering epistemology
is concerned with the
nature of engineering
knowledge (including the
technical, social, and ethical
aspects) and the ways of
engineering thinking (JEE,
2006).
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 10
Journal of Engineering Education (JEE). (2006). Special report: The research
agenda for the new discipline of engineering education. Journal of
Engineering Education, 95(4), 259–261.

11. Let it be assumed that there are five
qualities through which the mind
achieves truth in affirmation or denial,
namely techne (craftmanship/art or
technical skill), episteme (scientific
knowledge), phronesis (prudence),
sophia (wisdom), and nous (intelligence).
Aristotle, Nicomachean Ethics
(Book VI: Intellectual Virtues)
(Image source: Wikimedia Commons)
Harris Rackham (1996). Aristotle: The Nicomachean Ethics. Wordsworth.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 11

12. “Episteme” vs. “Techne”
• Scientific Knowledge (Episteme)
– What is scientifically knowable is learnable.
– Scientific knowledge can be communicated.
– For someone has scientific knowledge when he/she has the
appropriate sort of confidence, the origins are known to
him/her.
• Craftmanship / Art / Technical Skill (Techne)
– Craftmanship / art deals with bringing something into existence.
– To produce things deliberately in a way that can be explained.
– A craft concerned with things that are not exist by nature; its
origin is in the producer.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 12

13. What does it imply to
Engineering Education?
• Scientists investigate things which already exist;
• Engineers produce; based on true reasons; things
which do not exist.
– The three intellectual virtues: prudence (involves
judgment, understanding, and practical wisdom),
wisdom, and intelligence also play an important role
in the engineering profession.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 13

14. Graduate attributes of
engineering students
• A growing emphasis is being placed on engineering
graduates’ attributes by accreditation bodies,
employers, and also engineering students and
teachers.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 14

15. HKIE Graduate Attributes
(a) an ability to apply knowledge of mathematics, science, and engineering appropriate to the
degree discipline.
(b) an ability to design and conduct experiments, as well as to analyse and interpret data.
(c) an ability to design a system, component or process to meet desired needs within realistic
constraints, such as economic, environmental, social, political, ethical, health and safety,
manufacturability and sustainability.
(d) an ability to function on multi-disciplinary teams.
(e) an ability to identify, formulate and solve engineering problems.
(f) an ability to understand professional and ethical responsibility.
(g) an ability to communicate effectively.
(h) an ability to understand the impact of engineering solutions in a global and societal context,
especially the importance of health, safety and environmental considerations to both
workers and the general public.
(i) an ability to stay abreast of contemporary issues.
(j) an ability to recognize the need for, and to engage in life-long learning.
(k) an ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice appropriate to the degree discipline.
(l) an ability to use the computer/IT tools relevant to the discipline along with an understanding
of their processes and limitations.
Engineering
Disciplinary Knowledge
and Skills
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 15

16. HKIE Graduate Attributes
(a) an ability to apply knowledge of mathematics, science, and engineering appropriate to the
degree discipline.
(b) an ability to design and conduct experiments, as well as to analyze and interpret data.
(c) an ability to design a system, component or process to meet desired needs within realistic
constraints, such as economic, environmental, social, political, ethical, health and safety,
manufacturability and sustainability.
(d) an ability to function on multi-disciplinary teams.
(e) an ability to identify, formulate and solve engineering problems.
(f) an ability to understand professional and ethical responsibility.
(g) an ability to communicate effectively.
(h) an ability to understand the impact of engineering solutions in a global and societal context,
especially the importance of health, safety and environmental considerations to both
workers and the general public.
(i) an ability to stay abreast of contemporary issues.
(j) an ability to recognize the need for, and to engage in life-long learning.
(k) an ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice appropriate to the degree discipline.
(l) an ability to use the computer/IT tools relevant to the discipline along with an understanding
of their processes and limitations.
Holistic
Competencies /
Generic Skills
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 16

17. HKIE Graduate Attributes
(a) an ability to apply knowledge of mathematics, science, and engineering appropriate to the
degree discipline.
(b) an ability to design and conduct experiments, as well as to analyze and interpret data.
(c) an ability to design a system, component or process to meet desired needs within realistic
constraints, such as economic, environmental, social, political, ethical, health and safety,
manufacturability and sustainability.
(d) an ability to function on multi-disciplinary teams.
(e) an ability to identify, formulate and solve engineering problems.
(f) an ability to understand professional and ethical responsibility.
(g) an ability to communicate effectively.
(h) an ability to understand the impact of engineering solutions in a global and societal context,
especially the importance of health, safety and environmental considerations to both
workers and the general public.
(i) an ability to stay abreast of contemporary issues.
(j) an ability to recognize the need for, and to engage in life-long learning.
(k) an ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice appropriate to the degree discipline.
(l) an ability to use the computer/IT tools relevant to the discipline along with an understanding
of their processes and limitations.
Practical Skills
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 17

18. Forms of Ethical and
Intellectual Development
• Nine-position scheme (Perry, 1970)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 18
Perry, W. (1970). Forms of ethical and intellectual development in the college
years: A scheme. San Francisco: Wiley.
The modifying
of dualism
The realizing of
contextual
relativism
The evolving of
commitment

19. Social Epistemic Cognition (SEC)
• Definition: SEC is a human individual’s cognition and
cognitive processes related to epistemic matters
when situated in a social context (Chan et al., 2014).
R. Y.-Y. Chan, S. Li, D. Hui, “Social epistemic cognition in online interactions,” In Proceedings of the ACM SIGCHI Conference on
Human Factors in Computing Systems (CHI), 2014, pp. 3289-3298.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 19

20. Social Cognition
• Reciprocal determinism (Bandura, 1986)
Behavior (B)
Person (P)
Environment (E)
(Social environments)
Cognitive,
affective, etc.
Bandura, A. Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall, Englewood Cliffs, NJ, USA,
1986.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 20

21. Epistemic Cognition
• Three levels of human cognitive processing on information during
open-ended problem solving (Kitchener, 1983).
– First Level: Cognition
– Second Level: Metacognition
– Third Level: Epistemic Cognition
• Epistemic beliefs predict students’ learning (e.g. Hofer and Pintrich,
2002)
Kitchener, K.S. Cognition, metacognition, and epistemic cognition. Human Development, 26, 4 (1983), 222-232.
Hofer, B.K. and Pintrich, P.R. Personal Epistemology: The Psychology of Beliefs about Knowledge and Knowing. Erlbaum,
Mahwah, NJ, USA, 2002.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 21

22. Epistemic Cognition (EC)
Framework
• 5-component EC framework (Chinn et al., 2011)
rooted in Epistemology in Philosophy.
• Chinn’s EC Framework
– Epistemic aims and values
– Structure of knowledge
– Source, justification, and epistemic stances
– Epistemic virtues and vices
– Process of achieving epistemic aims
• EC is driven by epistemic aims.
C. Chinn, L. Buckland, and A. Samarapungavan, “Expanding the dimensions of epistemic cognition: arguments from philosophy
and psychology,” Educational Psychologist, vol. 46, no. 3, pp.141-167, 2011.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 22

23. More about Epistemic Aims
Minimally justified belief
Propositional knowledge
Understanding
Knowledge construction
Attainment to truth
High Level
Low Level
∞
• Hierarchy of epistemic aims.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 23

24. Social Epistemology
• Emphasizes on the social dimensions of beliefs
formation, knowledge acquisition, and information
processing (Fuller 2002; Goldman, 1999, 2011).
• Goldman’s tripartite Social Epistemology Framework
(Goldman, 2011)
– First Variety of SE: Individual Doxastic Agents (IDAs) with
Social Evidence
– Second Variety of SE: Collective Doxastic Agents (CADs)
– Third Variety of SE: Systems-Oriented (SYSOR) SE
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 24

25. Social Epistemology (SE)
Framework – Entities (1)
• Individual doxastic agents (IDAs) which are
individuals.
• Their internal doxastic attitudes (or belief states) can
be represented by external social evidence resulted
from the acts of communication; such evidence
include pages of print or messages on computer
screens.
Individual Social evidence
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 25

26. Social Epistemology (SE)
Framework – Entities (2)
• Collective doxastic agents (CDAs) which are a group of
individuals who have rational doxastic attitudes toward
sets of related propositions.
• Examples of CDAs include juries and communities.
• CDAs can be represented by the collective social
evidence* produced by the collective individuals.
Collective
individuals and
collective social
evidence
*Subjected to group rationality.
Illustration figure inspired by Palmer, The Courage to Teach: Exploring the Inner
Landscape of a Teacher’s Life
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 26

27. Social Epistemology (SE)
Framework – Entities (3)
• Epistemic systems are social systems that maintain
social practices, procedures, and patterns of inter-
agent influences that affect the epistemic outcomes
of the members in the systems.
Epistemic System
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 27

28. Knowledge and Knowing in
Online Communities
• What knowledge and knowing can be within and across (online)
communities (Chan, 2016).
R.Y.-Y. Chan, "Social epistemic cognition and engineering students' collaborative learning in emerging areas: An
implementation case study in a course for social networking", in Proceedings of the IEEE Frontiers in Education Conference,
2016, Erie, PA.

29. Social Epistemic Cognition
Illustrated
• Social epistemic cognition in epistemic systems.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 29
SEC

30. SEC – Small Data Analyses (Chan
et al., 2014)
• SEC can be mediated by online interactions (Chan et al., 2014)
– Measured with 32-items Epistemic Cognition Instrument (ECI),
validated (N = 563)
– 4-month Human-Computer Interaction (HCI) user study (N = 205)
– Chi-sq/df = 1.62, CFI = .98, SRMR = .05
– Significant mediation effect (z = 1.78, p < .05)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 30

31. To what extent do social epistemic
cognition (SEC) influence engineering
learning in the 21st century?
How can we design meaningful
engineering learning experience to
foster and assess engineering
students’ SEC?
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 31

32. SEC in Engineering Learning:
Analytics and Findings from
MOOC Big Data

33. MOOC and STEM-Related
Learning
• Massive Open Online Course (MOOC)
– online course, open access via the web
– Large variety of courses in STEM subjects
Coursera
13,274,775 participants
1,042 courses, 119 partners
Began with “Machine Learning”
Code.org
The Hour of Code
118,579,607 served
48% girls
Khan Academy
140,568 participants
(as of 2014)

34. Coursera MOOCs offered by
Chinese University of Hong Kong
https://www.coursera.org/cuhk
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 34

35. Case Study One
(Ding, Zhong, Chan, 2015; Zhong, Ding, Chan, 2015)
• Machine Learning MOOC
– Andrew Ng from Stanford
University
Date Duration Number of Distinct
Participants in Forums
Session One
Session Two
Session Three
14 Oct 2013 – 23 Dec 2013
3 March 2014 – 26 May 2014
16 June 2014 – 15 Sept 2014
10 Weeks
12 Weeks
13 Weeks
4,720
3,797
3,802
Session Four 22 Sept 2014 – 25 Dec 2014 12 Weeks 2,422
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 35
Zhong, J., Ding, J. and Chan, R.Y.-Y. (2015). Large-Scale Learning Process Analytics in MOOC Online Discourses. International
Workshop on Learning Analytics, Technology Adoption, and Language Learning in the Big-Data Era (LATALL 2015). Taipei.
Ding, J., Zhong, J. and Chan, R.Y.-Y. (2015). MOOC Learner Participation Lifecycle: What Can be Found from Large-Scale Temporal Social
Network Analysis? International Workshop on Learning Analytics, Technology Adoption, and Language Learning in the Big-Data Era (LATALL
2015). Taipei.

36. Temporal Social Network
Analysis (SNA)
• Perform a temporal social network analysis (SNA)
on our data in a weekly interval.
– Nodes represent the distinct participants within the
MOOC discussion forums.
– Directed ties represent the responses to an online
discourse from one participant to another.
– 10 sociomatrices are constructed to respectively
represent the resulted social network in 10 weekly
intervals.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 36

37. Temporal Social Network
Analysis (SNA)
Week 1 Week 2 Week 3 Week 4 Week 5
Week 6 Week 7 Week 8 Week 9 Week 10
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 37

38. SNA (Cont’)
Overall Sociograph (N = 4720)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 38

39. SEC – Content Analyses
• Developed an Epistemic Terms Dictionary
– Epistemic terms reflect the epistemic merit of a
statement (Chisholm, 2008)
– Our dictionary included 110 words that are related to
one’s epistemic engagement and justification.
– Developed by two researchers independently;
Cronbach’s alpha = .902
– Validated with small data (N=115) and confirmed
statistically significant relationship between
occurrence of epistemic terms in online discourse and
academic performance (r = .35, p < .005)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 39

40. SEC – Content Analyses
• Also produce:
– an keywords dictionary that indicates the concepts (by weeks)
learned from the course materials.
– A doxastic terms dictionary that contains word indicating beliefs
and attitudes (e.g. think, agree, disagree, etc.)
• Performed large-scale content analysis with Python and
Natural Language Processing (NLP) techniques.
• Each of the participants is represented by the discourse
he/she produced (α), with discourse scores calculated by:
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 40

41. SEC – Findings from MOOC
Content Analyses
• Occurrence of Week 1 to Week 5 keywords in discourse
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 41

42. SEC – Findings from MOOC
Content Analyses
• Occurrence of Week 6 to Week 10 keywords in discourse
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 42

43. SEC – Findings from MOOC
Content Analyses
• Epistemic Terms, Doxastic Terms, and First Week
Keywords (Fundamental Concepts)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 43

44. SEC – Findings from MOOC
Content Analyses
• Statistically significant relationship between
– epistemic terms and doxastic terms (r = .13, p < .001)
– epistemic terms and keywords (r = .15, p < .001)
– doxastic terms and keywords (r = .22, p < .001)
• Statistically significant relationship between
keywords and SNA indexes
– Outdegree (r = .05, p < .01)
– Indegree (r = .03, p < .05)
– Closeness (r = .13, p < .001)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 44

45. SEC in Engineering Learning:
Implementation Case in an
Undergraduate Course

46. SEC: Implementation Case in
Engineering Learning
• Student learning assessment can involve direct
and also indirect evidences.
• Based on the SEC framework, this course-level
implementation (Chan et al., 2017; Chan et al.,
2018) aims to collect and analyze direct as well as
indirect evidences of engineering student holistic
competencies at course level.
R.Y.-Y. Chan et al., “Direct evidence of engineering students’ generic skills learning: From research to practice in an
undergraduate course in information engineering,” in Proceedings of the IEEE Frontiers in Education Conference, 2017,
Indianapolis, IN.
R.Y.-Y. Chan et al., “Engineering Education for Sustainable Development and Global Citizenship:
A Course-Level Implementation Case in Hong Kong,” in Proceedings of the American Society for Engineering Education Annual
Conference and Exposition, 2018, Salt Lake City, UT.

47. Direct vs. Indirect Evidence of
Student Learning
• Indirect evidence (from which the fact can be inferred)
are collected by means other than looking at actual
student work.
– Offers signs that suggest students are probably learning.
– E.g., course evaluation, questionnaires on beliefs and attitudes.
• Direct evidence (evidence that support the assertion
directly without the need of any inference) are actual
student work evaluated using a standardized method or
rubric.
– Gives tangible and compelling indication that show what
students have learned.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 47
C. A., Palomba & T. W. Banta, Assessment Essentials: Planning, Implementing, and Improving Assessment in Higher Education.
San Francisco, CA: Jossey-Bass, 1999.

48. Direct Evidence of Student’s
Generic Skills Learning: The
Challenge
• While direct evidence of student learning are
often used to evaluate students’ mastery of
subject domain knowledge (e.g., assignments,
quizzes, final exam questions), its difficult to
collect direct evidence on students’ generic skills
learning.
How can I design assessment
items in my course to measure
students’ generic skills learning?
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 48

49. • Learning Outcomes
– (LO1) gain conceptual knowledge and theoretical
foundations in social media and human information
interactions and be able to apply them in explaining various
techno-societal phenomena.
– (LO2) be able to analyze and interpret social media contents
and social network structures.
– (LO3) be able to understand their professional responsibility
in sustainable development as information engineers.
– (LO4) be able to understand the impact of information
engineering solutions in a global and societal context.
– (LO5) be able to stay abreast of contemporary issues and
formulate professional recommendations and/or action
plans based on human information behaviours.
• Enrollment: 78 students majored in Information
Engineering and Computer Science (minor IE).
IERG3320 Social Media and Human
Information Interactions (2017-18)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 49
Generic skills/
Holistic
competencies
oriented

50. Implementation Case: Teaching
and Learning Context
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 50
Introduction
Social media and
HII
Environments,
elements, and
information
Big data for
sustainable
development
Recommendation
Systems
Information and
human cognition
Physical
Information
Semantic
Information
Natural language
processing
Digital
Information
Sentiment
analysis
Social media
analytics
Social Network
Analysis (SNA)
Big data
visualization:
Selected cases
from UNSD
Information
visualization
(1) Blog posting (week 1 to 8)
(2) Post commenting (week 2 to 10)
(3) Social Media & HII for SD (Submission deadline: week 12)
(4) Social Media Analytics (Submission deadline: week 14)
Conceptual
Knowledge
Practical
Knowledge
Assessments
TimeWeek 1 Week 14
Linkage between
conceptualand
practicalknowledge
Keys
Subjectknowledge
(5)Final
Examination

51. Social Media and HII for
Sustainable Development
(Group Project)
• Selected group project
topics (Policy Reports)
– Emission: An enemy of
modern world (SDG 3, 13)
– Urban-rural divide and
social media affordances in
market analysis (SDG 1, 4,
13)
– A charity mobile app for
access to safe water in
Kenya (SDG 3, 6, 9)
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 51

52. Measures
• The following direct and indirect evidences which
measure students’ generic skills were collected and
analyzed:
1. (Direct evidence) Blog post contents (as e-portfolios)
which include students’ own learning reflections and self-
collected external reference materials.
2. (Direct evidence) Online comments which reflects
students’ evaluation on their peers’ learning reflection (a
dataset with 1105 messages in course context).
3. (Direct evidence) Topological structure of the resulted
online social network (78 nodes and 1105 edges).
4. (Indirect evidence) Questionnaire on students’ beliefs
associated to SEC and collaborative learning.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 52

53. Social Network Analysis
(Direct Evidence)
• A blogger social network which is a directed graph
with 78 nodes and 1105 edges was established.
– The nodes correspond to the participating students
– The directed edge represents a “comment to” relationship
between a comment provider and a comment receiver.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 53

54. Class Blogging Community
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 54

55. Student SEC Beliefs and Collaborative
Learning (Indirect Evidence)
• Descriptive statistics (students’ beliefs associate
to SEC and Collaborative Learning)
Note: Cronbach’s alpha values for pretest and posttest items are 0.87 and 0.80, respectively.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 55

56. Relationship between Learning
Beliefs and Behaviors
• A significant relationship between SEC gains and
social networking behavior was identified.
• Participant out-degree was significantly
correlated to belief gains in justification of social
knowledge (r = .44, p < 0.05) and social epistemic
virtues (r = .41, p < .05), respectively.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 56

57. Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 57
SEC
Theory
Learning Analytics
Learning Design
(Implementation Case in
Engineering Education)
Engaging Learning
&
Empowering
Change

58. Takeaway 1
• Social epistemic cognition connects epistemic
cognition, social epistemology, and social
cognition.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 58

59. Takeaway 2
• Students’ intellectual virtues can be nurtured by
engaging them in self-reflection on their
professional role and identity.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 59
What is engineering and
what does it mean to me
as an engineering student?

60. Takeaway 3
• Students’ SEC can be promoted (and analyzed)
by establishing an online learning community.
Social Epistemic Cognition in Engineering Learning | Rosanna Yuen-Yan Chan | CITERS 2018 60

61. THANK YOU!