1. Promoting Active Learning through Self-Assessment and Peer-Instruction: design, evidence, and evaluation
Dr Fabio R.
#altalc – Sep 2017

2. YOUR PRESENTER Fabio Aricò
National Teaching Fellow Senior Lecturer in Macroeconomics School of Economics – University of East Anglia, UK
Research fields
Higher Education policy and practice (widen. access, satisfaction)
Technology Enhanced Learning
Self-Assessment and Academic Self-Efficacy

3. ACKNOWLEDGEMENTS HEA – Teaching Development Grant Scheme
HEFCE Piloting and Evaluating Measures of Learning Gain
UEA Students, Alumni, and Research Assistants

4. AIMS & OBJECTIVES
My talk will be all about pedagogies which I have designed, used, and evaluated. They are now being rolled across different disciplines.
Sharing my practice  take home at least one idea!
Inspiring research  from research-led teaching to teaching-led research
Support developments in the HE sector  in the UK: TEF is coming (learning gain)
Support personal development  promoting and evidencing excellence.

5. THE GENERAL PICTURE Active Learning Self-Assessment Peer-Instruction
and Class Flipping X X

6. OUTLINE
1. Peer-Instruction & Self-Assessment in an Active Learning Environment
2. Self-Efficacy and Self-Assessment
 attainment and confidence levels
 objective and subjective measures of confidence
3. Peer-Instruction, Learning Gain & Confidence Gain
4. Student appraisal of the pedagogies
5. Closing the feedback loop
6. Summary of empirical findings.

7. ETHICAL REMARK
You will be presented with data collected during teaching sessions.
Students involved have given informed consent for me to analyse their responses and present the results of this analysis.
I can assist with ethical queries as well, please ask me.

8. Active Learning Environment
1. Peer-Instruction & Self-Assessment in an
Active Learning Environment

9. FLIPPED CLASS and PEER-INSTRUCTION
Flipped classroom & Peer-Instruction  pre-reading + student interaction  Mazur (1997)  Henderson and Dancy (2009)
 well-developed research in Physics and STEM.
Learning analytics for Peer-Instruction  Learning gains: Mazour Group - Bates & Galloway (2012)
 Student satisfaction: Hernandez Nanclares & Cerezo Menendez (2014).
There is not much literature on the links with self-assessment skills Open field, with many unanswered questions  e.g. role of demographics, language, previous background
 Pedagogically: self-assessment blends with flipping and Peer-instruction.

10. SELF-EFFICACY and SELF-ASSESSMENT
Academic Self-Efficacy = confidence at performing academic
tasks and/or attaining academic goals.
Bandura (1977) 1. Mastery of experiences
2. Vicarious experiences
3. Verbal persuasion
4. Environment and settings
See also: Pajares (1996) and Ritchie (2015).
Idea: Students should develop their self-efficacy to master their
learning experience. Measure learning gain along with increased self-efficacy: ‘confidence gain’.

11. LEARNING GAIN Policy-driven research to assess student learning
Arum & Roksa (2010), ‘Academically Adrift’ (US data)
OECD approach: assessment of learning outcomes AHELO Project (OECD, 2011 and 2014)
US & UK approach: learning gain (‘distance run’ over time)
McGrath et al., 2015
HEFCE commissioned research on piloting measures of learning gain
Outputs to feed in Teaching Excellence Framework.

12. ACTIVE LEARNING ENVIRONMENT
Introductory Macroeconomics (from 2013 to 2017)
year-long module (compulsory 1st year)
250 students (started with 140 in 2013, 250 past 2yrs)
22 lectures (2hrs per week)
8 seminars (every second week, even)
8 workshops (every second week, odd)
Students endowed with individual Audience Response Systems (clickers)
 continuous data collection facilitated by technology;  comprehensive ethical approval obtained beforehand.

13. WORKSHOPS – teaching algorithm
Round 1 - formative question
- 4 choices
- no information
- no answer
Peer-Instruction - students talk
- compare answers
- explain each other
Self-Assessment 2 - confidence question
- 4 level Likert-scale
- information shared
Self-Assessment 1 - confidence question
- 4 level Likert-scale
- information shared
Round 2 - formative question
- Identical to R1
- information shared
- correct answer

14. Holding everything else constant in the world economy: If inflation in a country increases, its…
exports decrease and imports stay the same;
exports decrease and imports increase;
exports increase and imports decrease;
imports increase.

15. “I think I have the skills/knowledge to answer the previous question correctly”
strongly agree;
agree;
disagree;
strongly disagree.

16. Holding everything else constant in the world economy: If inflation in a country increases, its…
exports decrease and imports stay the same;
exports decrease and imports increase;
exports increase and imports decrease;
imports increase.

17. “NOW I think I have the skills/knowledge to answer the previous question correctly”
strongly agree;
agree;
disagree;
strongly disagree.

20. WORKSHOPS – asking the right questions
Bloom’s Taxonomy
Aim to climb up the pyramid
Do not trivialise MCQs.
See talk by Simon Lancaster!

21. DATASETS AND CODING Student Q1 Q2 Q3 …  performance per student
confidence by student
Formative questions
1 = correct 0 = incorrect
Confidence questions
1 = strongly/agree
0 = strongly/disagree … … 
performance per question
confidence by question

22. PART A – attainment and confidence
2. Self-Efficacy and Self-Assessment Skills
PART A – attainment and confidence

23. WORKSHOPS – data coding
For each session (7 in a year in , 8 from ):
Code 1st response: 1 = correct = incorrect
Code confidence in response: 1 = strongly/agree
0 = strongly/disagree
Compute average score and average confidence per student.
attainment self-assessment
measure measure

24. WORKSHOPS – data coding
For each student (in each session):
If student average score > session average score  high-attainment
otherwise low-attainment
If student average conf. > session average conf.  high-confidence
otherwise low-confidence

25. WORKSHOPS – data analysis
Cross-tabulate results:

26. WORKSHOPS - results
What is the relationship between attainment and confidence?
No Dunning-Kruger Effect!

27. WORKSHOP - results
What is the relationship between attainment and confidence?

28. WORKSHOPS – compared with Seminars
7 Seminars running alternated to Workshops.
Paper-based assessment – 5-6mins – 4 questions.

29. WORKSHOPS – compared with Seminars
7 Seminars running alternated to Workshops
Paper-based assessment – 5-6mins – 4 questions.
In WORKSHOPS  no Dunning-Kruger Effect
In SEMINARS  there is Dunning-Kruger Effect.
 The modes of delivery for the same type of assessment change the self-assessment outcome.

30. PART B – confidence and entropy
2. Self-Efficacy and Self-Assessment Skills
PART B – confidence and entropy

31. WORKSHOPS – data coding and modelling
For each 1st response question (4-10) across all sessions (7 in a year in ):
Compute entropy index across responses (A,B,C,D)  objective measure of confidence
Compute average confidence per question  subjective measure of confidence
Model: confidence = f ( entropy ) + session-dummies

32. WORKSHOPS – results
confidence = f ( entropy ) + session-dummies

33. 3. Peer-Instruction Learning Gain &
Confidence Gain

34. OPERATIONALISING TWO GAINS
For each 1st and 2nd response to formative assessment questions: % correct R2  % correct R1
Normalised Learning Gain (NLG) =
100%  % correct R1
For each 1st and 2nd response to self-assessment questions: % confident R2  % confident R1
Normalised Confidence Gain (NCG) =
100%  % confident R1

35. PEDAGOGY EVALUATION STRATEGY
Is the pedagogy developing good self-assessment skills? Are students self-assessing correctly over Round 1/2?
Is peer-instruction able to generate learning/confidence gain? How does learning/confidence gain relate to initial knowledge/confidence levels (Round 1)?
Is learning gain associated to confidence gain? Does the structure of the algorithm affect this relationship? Vicarious of Experience Scenario (VES)
2017 Mastery of Experience Scenario (MES) only contrasted with VES (4 sessions each).

36. WORKSHOPS – contrast 2 teaching algorithms
VES
MES
Round 1 - formative question
- 4 choices
- no information
- no answer
Peer-Instruction - students talk
- compare answers
- explain each other
Self-Assessment 2 - confidence question
- 4 level Likert-scale
- information shared
Self-Assessment 1 - confidence question
- 4 level Likert-scale
- information shared
Round 2 - formative question
- Identical to R1
- information shared
- correct answer

37. RESULT – Self-assessment Skills Round 1
2016 VES =0.429*** R²=0.56
% confident
Round 1
2017 VES =0.367*** R²=0.59
2017 MES =0.09***
0.44
0.33
% correct Round 1

38. RESULT – Self-assessment Skills Round 2
% confident
Round 2
2016 VES =0.282*** R²=0.26
2017 VES =0.322*** R²=0.64
0.60
2017 MES =1.44***
0.57
% correct Round 2

39. RESULT – Normalised Gains in 2016
NLG R²=0.39
NCG R²=0.19
0.85
NCG
0.52
NLG
% Correct/Confident in Round 1

40. RESULT – Normalised Gains in 2017
NLG R²=0.21
NCG R²= =0.132**
NCG
0.67
NLG
% Correct/Confident in Round 1

41. RESULT – Learning Gain & Confidence Gain
NCG
2016 R²=016
2017 VES =0.19*** R²=0.39
MES =0.125**
0.31
0.28 -1
NLG

42. REFLECTION
The active learning environment discussed today combines two powerful pedagogies: self-assessment and peer-instruction.
The role of the teacher does affect confidence levels, which are higher when s/he demonstrates (VES).
Alterations of the role played by the teacher in either VES or MES do not compromise the effective interaction between students and the benefits generated by the active learning components of the pedagogy. Students support each other in their learning and develop confidence beliefs along with skills.

43. 4. Student appraisal of the pedagogies

44. WHAT DO STUDENT THINK?
The literature on evaluation of TEL and Peer-Instruction is far too focused on whether students ‘enjoy’ their experience (student satisfaction)
 typical of academic practice literature.
I want to give more focus on the perception of learning:
 1st lecture: introduced the concept of Peer-Instruction asked the students to share what they think of it.
 each workshop: asked students to share their view on the session and whether they felt they learnt from each other.
 informal end-of-module feedback: what was the most effective component of the blended learning environment mix within the module.

45. 1st lecture: “‘Peer-instruction’ sessions (students teaching each other) are more effective than lectures (teacher teaching students)”
No. Respondents = 82

46. Workshop feedback statement: “I have learnt more Economics by discussing answers with my classmates”

47. Comparing student opinion about Peer-Instruction as an effective pedagogy before and after exposure

48. End-of-module Feedback: What is the component of the Macro module which had the strongest impact on your learning?

49. 5. Closing the Feedback Loop

50. FEEDBACK to STUDENTS During polling sessions:
 show results, talk to the students, encourage them;
 use comparative-links, show them their progress;
 explain what you are doing and why you are doing it.
After polling sessions:
 share session reports on your VLE and comment on these;
 use mail-merge to send individual reports;
Go beyond polling:
 craft your own perfect pedagogical blend;
 be aware of different student needs.

51. 6. Summary of Empirical Findings

52. SUMMARY of RESULTS
In both Round 1&2, confidence levels are lower under MES. However, performance and confidence are consistently positively correlated  students self-assess correctly, irrespectively of MES/VES scenario.
Peer-instruction generates higher learning/confidence gain when initial knowledge/confidence in the classroom is neither too high or too low  ‘sweet-spot’ pattern does not depend on MES/VES scenario.
Under MES scenario confidence gain is lower, compared to VES scenario. However, confidence gain is consistently positively correlated to learning gain  students develop more confidence as they learn, irrespectively of MES/VES scenario.
The pedagogy appears to be robust to teacher intervention  Active Learning!

53. FINAL REMARKS
It took me 4 years to develop this teaching approach & evaluation. Think big….but start small, and build from there.
It’s not about the technology, it’s about the pedagogy and, most importantly, it’s about the students.
Be concerned about ethics, but do not be discouraged or scared (students are not: JISC, 2016).
Choose your demonstrators carefully: your ‘average Fabio’ might be more convincing than a pedagogy expert or a techno-hyper-enthusiast.

54. STAY IN TOUCH! F.Arico@uea.ac.uk @FabioArico
“Promoting Active Learning Through Peer-Instruction and Self-Assessment: A Toolkit to Design, Support and Evaluate Teaching”, Educational Developments, SEDA, 17.1,

55. Promoting Active Learning through Self-Assessment and Peer-Instruction: design, evidence, and evaluation
Dr Fabio R.
#altalc – Sep 2017