Mastery Grids: An Open SourceSocial Educational Progress Visualization

Tomasz D. Loboda, Julio Guerra, Roya Hosseini, Peter

BrusilovskyPAWS Lab,

University of Pittsburgh

Overview

• The past– Why we are doing it?

• The paper– Mastery Grids and its evaluation

• Today’s state– What we have done since submitting the

paper?• The future

– What are the plans and invitation to collaborate

The Past

• Why?– Increase user performance– Increase motivation and retention

• How?–Adaptive Navigation Support–Topic-based Adaptation–Open Social Student Modeling

Adaptive Link Annotation: InterBook

1. Concept role

2. Current concept state

3. Current section state4. Linked sections state

4

3

2

1

√

Questions of the current quiz, served by QuizPACK

List of annotated links to all quizzes available for a student in the current course

Refresh and help icons

QuizGuide = Topic-Based ANS

Topic-Based Adaptation

Concept A

ConceptB

ConceptC

Each topic is associated with a number of educational activities to learn about this topic

Each activity classified under 1 topic

QuizGuide: Adaptive Annotations• Target-arrow

abstraction:– Number of arrows –

level of knowledge for the specific topic (from 0 to 3). Individual, event-based adaptation.

– Color Intensity – learning goal (current, prerequisite for current, not-relevant, not-ready). Group, time-based adaptation.

Topic–quiz organization:

QuizGuide: Success Rate

QuizGuide: Motivation

Within the same class QuizGuide session were much longer than QuizPACK sessions: 24 vs. 14 question attempts at average.

Average Knowledge Gain for the class rose from 5.1 to 6.5

• Topic-Based interface organization is familiar, matches the course organization, and provides a compromise between too-much and too-little

• Two-way adaptive navigation support guides to the right topic

• Open student model provides clear overview of the progress

Topic-Based ANS: Success Recipes

Concept-based student modeling

Example 2 Example M

Example 1

Problem 1

Problem 2 Problem K

Concept 1

Concept 2

Concept 3

Concept 4

Concept 5

Concept N

Examples

Problems

Concepts

NavEx = Concept-Based ANS

• To investigate possible influence of concept-based adaptation in the present of topic-based adaptation we developed two versions of QuizGuide:

Topic-based Topic-based+Concept-Based

Concept-based vs Topic-based ANS

Social Guidance

• Concept-based and topic-based navigation support work well to increase success and motivation

• Knowledge-based approaches require some knowledge engineering – concept/topic models, prerequisites, time schedule

• In our past work we learned that social navigation – “wisdom” extracted from the work of a community of learners – might replace knowledge-based guidance

• Social wisdom vs. knowledge engineering

Open Social Student Modeling

• Key ideas– Assume simple topic-based design – Show topic- and content- level knowledge

progress of a student in contrast to the same progress of the class

• Main challenge– How to design the interface to show student

and class progress over topics?– We went through several attempts…

16

QuizMap

17

Parallel Introspective Views

18

Progressor

• Topic organization should follow the natural progress or topics in the course

• Clear comparison between “me” and “group”

• Ability to compare with individual peers, not only the group

• Privacy management

OSLM: Success Recipes

The Value of OSLM

Progr

esso

r

QuizJE

T+IV

QuizJE

T+Porta

l

Java

Guide

0

50

100

150

200

250

205.73

113.05

80.81

125.5

Attempts

AttemptsPro

gres

sor

QuizJE

T+IV

QuizJE

T+Porta

l

Java

Guide

0.00%

20.00%

40.00%

60.00%

80.00%68.39% 71.35%

42.63%

58.31%

Success Rate

Success Rate

The Secret

MasteryGrids

• Adaptive Navigation Support• Topic-based Adaptation• Open Social Student Modeling• Social Educational Progress

Visualization• Multiple Content Types• Open Source• Concept-Based Recommendation• Multiple Groups

The Study

• Fall 2013, 3 classes• Java Programming

– 19 topics,75 examples and 94 QiuzJet problems

• Databases– 19 topics, 64 examples, 46 SQL-Knot

questions.• Offered as an addition to the traditional

portal access (called “Links” in the paper)• Incentive: 5 points out of 100 to solve 15+

problems – either Links or MG

Accessing MG interface from Links

Usage

Usage Groups in Java Class

• (Z) 4 students did not use either of the tools • (L1) 2 students used Links only and never used

visualization• (L2) 3 students used Links for content access, loaded

the visualization, did not use it• (L.MG1) 16 students used Links for content access,

interactively explored MG, did not use it for content access

• (L.MG2) 6 students used both Links and Mastery Grids for content access

• (MG) 5 students used exclusively Mastery Grids for content access.

Group-Based Analysis

• 5 (L1+L2) had little to no use of Mastery Grids

• 26 (L.MG1+L.MG2+MG) used it considerably

• Students who used the visualization seemed to be more engaged with self-study content– answered more questions– tried more examples– inspected more example line comments– got a higher correct question answer ratio.

Subjective Responses

• High level of “good” responses• A number of “poor” responses to specific

features which guided our work in 2014

More MG Activity = Better Grade?

• How? – Pooled data from all three courses– Only students who logged in at least once– Fitted four linear mixed models

• Separately considered content and interface– Only content access through Links or MG– All activity with MG

What we are doing now?

• Enhanced Interface after two semesters of learning and student feedback

• Easy authoring to define “your course”• Exploring more advanced guidance and

modeling approaches based on large volume of social data

• Interface and cultural studies in a wide variety of classes from US to Nigeria– Interested to be a pilot site? Write to

peterb@pitt.edu

MG flexibility

• Parameters to set the visualization:– show hide toolbar or any of its elements– set the (sub) groups: top N, other sub groups– preset values (for example load individual

view by default)– enable/disable recommendation

• Parameters can be specified by group or by user

Course Authoring Interface

A label showing that you are the creator of the

course

domain

Institution code

Course

codeCourse title

Number of Groups

using this course

Creator name

Acknowledgements

• Past work on ANS and OSLM– Sergey Sosnovsky– Michael Yudelson– Sharon Hsiao

• Pitt “Innovation in Education” grant• NSF Grants

– EHR 0310576– IIS 0426021– CAREER 0447083

• ADL “PAL” grant to build MasteryGrids

Try It!

• GitHub link Twitted

• Brusilovsky, P., Sosnovsky, S., and Yudelson, M. (2009) Addictive links: The motivational value of adaptive link annotation. New Review of Hypermedia and Multimedia 15 (1), 97-118.

• Hsiao, I.-H., Sosnovsky, S., and Brusilovsky, P. (2010) Guiding students to the right questions: adaptive navigation support in an E-Learning system for Java programming. Journal of Computer Assisted Learning 26 (4), 270-283.

• Hsiao, I.-H., Bakalov, F., Brusilovsky, P., and König-Ries, B. (2013) Progressor: social navigation support through open social student modeling. New Review of Hypermedia and Multimedia [PDF]

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