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1 Assessing Student Self-Assessment: An Additional Argument for Blended Learning Fabio R. Aricò Duncan Watson Chris Thomson NRHE SRHE Dec 2014

Assessing Student Self-Assessment: An Additional Argument for Blended Learning - FR Arico

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Page 1: Assessing Student Self-Assessment: An Additional Argument for Blended Learning - FR Arico

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Assessing Student Self-Assessment:

An Additional Argument for

Blended Learning

Fabio R. Aricò

Duncan Watson

Chris Thomson

NRHE SRHE – Dec 2014

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ACKNOWLEDGEMENTS

UEA-HEFCE Widening Participation Teaching Fellowship

HEA – Teaching Development Grant Scheme

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OUTLINE

1. Overview of the “When Student Confidence Clicks Project”

2. Introduction to 2 learning environments to be compared:seminars and workshops

Learning analytics:the relationship between attainment & self-assessment

4. Final remarks: assessing self-assessment

5. Further research

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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.

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1. When Student Confidence Clicks: the role of Academic Self-Efficacy in Learning

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PROJECT DEVELOPMENTS

Project Resources: https://sites.google.com/site/fabioarico/hea_tdg

Project Workshop: Wednesday 3 Sep 2014 - University of East Anglia

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BLENDED LEARNING ENVIRONMENT

• Intense use of Student Response Systems (clickers).

• Focus on increasing students’ Academic Self-Efficacy beliefs Self-Assessment is a fundamental component.

• Intense use of SRS + VLE dialogue with the students – closing feedback loop blended learning, but also blended surveying!

• Learning analytics to disentangle relationship between different aspects of the learning experience.

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DATASETS

Student Q1 Q2 Q3 …

1 0 1 1

2 1 0 0

3 1 1 …

performance per questionconfidence by question

pe

rform

ance

pe

r stud

en

tco

nfid

en

ce by stu

de

nt

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longitudinal study- across all lectures- across all seminars- across all workshops

Intermediate and final attainment outcomes- course test- final exam

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EVIDENCE-BASED PRACTICE

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ATTAINMENT

ENGAGEMENT CONFIDENCE

Gender

Satisfaction

Previous attainmentDomicilePOLAR

Perceived difficulties

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2. Workshops and Seminars

Attainment & Self-Assessment

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MOTIVATION and CORE IDEAS

• This is a by-product of my HEA TDG project, which is taking life on its own Self-Assessment as an important determinant of Self-Efficacy beliefs

(Bandura, 1977 – Pajares, 1996)

• Self-Assessment skills contribute to form autonomous students HE learning and teaching practice should develop these

(Boud, 1995 – Boud and Falchikov, 2006/7 – Evans, 2013)

• Empirical evidence seems to identify positive association between self-assessment skills and performance in academic settings Dunning et.al. (2003), Zell & Krizan (2014)

• Challenge: does (self)assessment design have a role to play?

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TEACHING PROTOCOL – the module

Introductory Macroeconomics Level 1 – compulsory year-long module - 170 students

Lectures traditional frontal-teaching (10 per sem.)

Seminars small group, pre-assigned problem sets (4 per sem.)

Workshops large group, problem-solving sessions (4 per sem.)

Support Sessions non-compulsory drop-in sessions (4 per sem.)

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WORKSHOPS – learning environment

• Large flipped-class environment (2 Groups - 85 students each)

• 1st part: Multiple choice questions (4 choices) - 2nd part: problem-solving

• Iterated algorithm:

1. Ask Question 1st round 4 choices (distribution not revealed)

2. Ask Self-Assessment Question 4 levels Likert-scale (strongly/agree – strongly/disagree)

3. Peer-Instruction

4. Ask Question 2nd round show answers – teach correct answer and give explanations.

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WORKSHOPS – data coding

For each session (7 in a year):

• Code 1st response: 1 = correct 0 = incorrect

• Code confidence in response: 1 = strongly/agree0 = strongly/disagree

• Compute average score and average confidence per student.

attainment self-assessmentmeasure measure

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WORKSHOPS – data coding

For each student (in each session):

If student average score > session average score high-attainmentotherwise low-attainment

METHOD A:

If student average conf. > session average conf. high-confidenceotherwise low-confidence

METHOD B:

If student average conf. > 0.5 high-confidenceotherwise low-confidence

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WORKSHOPS – data analysis

Cross-tabulate results:

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WORKSHOPS - results

What is the relationship between attainment and confidence?

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WORKSHOP - results

What is the relationship between attainment and confidence?

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SEMINARS – learning environment

• Small-class environment (Groups of 13-15 students each)

• 1st part: Multiple choice quiz (4 choices) - 2nd part: problem-solving

• Structure of the Quiz:

- Paper based

- 5-6 minutes duration

- 3 or 4 formative questions

- 1 self-assessment question on the quiz

- 1 self-efficacy question about future beliefs.

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SEMINARS – data coding

For each session (7 in a year):

• Code each answer: 1 = correct 0 = incorrect

• Code confidence in response: 1 = strongly/agree0 = strongly/disagree

• Compute average score attainment measure

There is just one confidence response confidence measure

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SEMINARS – data coding

For each student (in each session):

If student average score > session average score high-attainmentotherwise low-attainment

If student confidence = 1 high-confidenceotherwise low-confidence

Note the asymmetry with workshops.This was addressed this year, asking about confidence question by question.

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SEMINARS - results

What is the relationship between attainment and confidence?

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SEMINARS - results

What is the relationship between attainment and confidence?

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3. Final Remarks

Assessing Self-Assessment

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PREVIOUS LITERATURE

• In literature there is a prevailing idea:

low-attainment students are not able to self-assess their performance.

• Dunning, D., Johnson, K., Ehrlinger, J., and Kruger, J., (2003), “Why People Fail

to Recognise their Own Incompetence”, Current Directions in Psychological

Science, 12:83, 83-87.

• But the results find in my research seem to question the learning

environment within which self-assessment is being observed.

the learning environment affects the relationship attainment-confidence.

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OVERALL RESULTS

• In Seminar Quizzes:

high-attainment students display higher confidence

low-attainment students not able to self-assess their performance.

• In Workshop sessions:

high-attainment students display higher confidence

low-attainment students display lower confidence.

• How to interpret this asymmetry?

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OVERALL RESULTS

• In Seminar Quizzes:

3 or 4 questions, paper-based quiz, 5-6 minutes, not anonymous, small class

1 confidence assessment for overall performance.

• In Workshop sessions:

5-10 questions, clicker response, slower pace, quasi-anonymous, large class

1 confidence assessment for each question asked.

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OVERALL RESULTS

• Low-attainment students encounter more difficulties in

self-assessing their performance in an environment where:

they self-assess their ‘overall’ performance on a composite task

they are exposed to questions for a shorter period of time

they are exposed to fewer questions, not anonymously.

• Focus group interviews (differentiated by attainment groups)

confirm that low-attainment students display poorer self-assessment skills.

• So what is happening in workshops?

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4. Further Research

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FURTHER RESEARCH

• Introduce confidence evaluation question-by-question in Seminars.

• Explore the relationship between objective and subjective evaluation

relationship between response entropy and student confidence.

• “Peer-Instruction Unveiled”

relationship between 1st and 2nd response – ‘learning gains’

relationship between learning gains and student confidence.

• Learning analytics at student-level

investigate the role of demographics

investigate the impact of formative assessment on summative assessment.

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