tracing self-regulated learning in responsive open learning environments

Lehrstuhl Informatik 5(Information Systems)

Prof. Dr. M. Jarke1

LearningLayers

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Tracing Self-Regulated Learning in Responsive Open Learning EnvironmentsDominik Renzel, Ralf Klamma, Milos Kravcik

Advanced Community Information Systems (ACIS) GroupRWTH Aachen University, Germany

Alexander NussbaumerKnowledge Technologies Institute (KTI)

Technical University Graz

ICWL 20155-8 November, 2015Guangzhou, China

http://creativecommons.org/licenses/by-sa/3.0/





http://dbis.rwth-aachen.de/cms/research/MiCIS


http://www.role-project.eu/

http://learning-layers.eu/



Prof. Dr. M. Jarke2

LearningLayers

Motivation Self-Regulated Learning (SRL) increases learner effectiveness SRL challenging to facilitate in conventional technology enhanced

learning (TEL), e.g. learning management systems like moodle– Lack of individualized approach– Lack of balance between learner’s freedom and guidance

High SRL potential: Personal Learning Environments (PLE)– Inherently designed for personalization & adaptation– Customization & multi-mode/level learner guidance with SRL widgets

Research gaps:– SRL operationalization in PLE – Lack of longitudinal study on SRL in naturalistic PLE settings







Prof. Dr. M. Jarke3

LearningLayers

Contributions

SRL process model for PLE operationalization

1.5-year naturalistic study tracing SRL in PLE

Guidelines for SRL support in PLE







Prof. Dr. M. Jarke4

LearningLayers Web Widget-Based PLE –

Responsive Open Learning EnvironmentsROLE PLE Management Platform (ROLE SDK/Sandbox)

ROLE Widget StoreWidgets Widget Bundles

Widget Metadata

Widget Space







Prof. Dr. M. Jarke5

LearningLayers

Widget Store (Metadata)Widget Space (Context)

Self-Regulated Learning in ROLE – Cyclic Process Model

Theoretical foundations:– Zimmerman’s 3-phase cyclic process model (Zimmerman, 2002)– Aviram’s SRPL extension by self-profile for indicating preferences (Aviram 2008)

Mediation between pedagogical constructs & concrete learning tools Separation of concerns: widget developers vs. pedagogical experts

Taxo

nom

y of

le

arni

ng s

trate

gies

& te

chni

ques Widget/Bundle

Functionality

Learning phaseLearning strategy

Legend







Prof. Dr. M. Jarke6

LearningLayers ROLE Sandbox Analysis –

Data Sampling Method

SRL traceable from standard protocol log data recording PLE use?







Prof. Dr. M. Jarke7


Data Set OverviewIndividual Use

Institutional Use

• 1.5 years (03/12 - 09/13)• 1.72 mio API requests• > 3900 IP addresses• > 600 cities; >80 countries• No bots & project partners• Pure API requests







Prof. Dr. M. Jarke8


Active Spaces, Users, Operations

178

…created spaces

251

…joined spaces

320

…added widgets

1231

…used spaces1324 active users…

682

…70% active spaces

Participation inequality Few potential SRL users (4-8%)

974 widget spaces…

SRL SRL







Prof. Dr. M. Jarke9


Widget Use by Functionality Groups

Widget functionality groupSRL/Non-SRL WidgetWidget assigned to functionality group

/

Legend

634 different widgets deployed in spaces 40 widgets assigned to 7 function groups Widget node size ~ #widget adds to spaces Function node size ~ #widgets assigned 40 SRL-related widgets (6.3%) Un/assigned widgets added less/more Assigned widgets with clear purpose Improved guidance with recommendation

backed by SRL-related metadata Potentially helpful widgets remain

undiscovered without metadata







Prof. Dr. M. Jarke10


SRL Spaces vs. Non-SRL Spaces

Significantly more demand for planning and self-reflection in SRL spaces Stronger focus on reliance upon functionality groups for widget selection Slightly less demand for collaboration and communication in SRL spaces

– Contradictory to observation that SRL spaces mostly used by single learners No significant differences in other functionality groups









Widgets added/used by Users Bipartite undirected graph: widget added/used by user 22 connected components (1 giant, 21 satellites)

SRL widget adders/users more active in PLE design SRL widget adders/users more serendipitous

Giant Component Satellites

Users end-users (learners, facilitators) & professional developers individual developers

Activity 320 users actively added/removed widgetsUsage patterns hinting to informal learning

Few widget adds, frequent (re)load Typical develop/test routine

SRL Activity 63 users added SRL widgets (29 more than one)123 users used SRL widgets








LearningLayers Guidelines to Support SRL in Personal

Learning Environments1. Empower learner to personalize and adapt their PLE (e.g. nudging)2. Allow individual skill-based balancing of guidance & freedom3. Never be prescriptive (libertarian paternalism)4. Provide different means for different guidance levels

– Automated/social recommender (+ metadata!)– SRL tools for preparation, planning, learning, reflection

5. Stimulate meta-cognition (reflection on SRL processes)– Stimulate awareness by providing appropriate feedback– Stimulate intrinsic motivation with balanced guidance & freedom

6. Support online collaboration7. Support best-practice sharing & re-use








LearningLayers

Conclusions SRL process model & operationalization in PLE SRL traceable from standard protocol log data (deeper analysis needed) SRL guidelines for PLE (personalization, guidance & freedom, meta-

cognition, awareness, motivation, collaboration & best practice sharing) ROLE Sandbox used by follow-up EU TEL projects (Learning Layers,

BOOST, METIS, etc.) & unknown end-users worldwide Since 03/12 - open end: ROLE Sandbox (http://role-sandbox.eu/)

development & operation ( continuous data collection) More studies & results in our CoRR paper:

A Framework for Facilitating Self-Regulation in Responsive Open Learning Environments (http://arxiv.org/abs/1407.5891)

http://role-sandbox.eu/

http://role-sandbox.eu/

http://arxiv.org/abs/1407.5891

http://arxiv.org/abs/1407.5891






tracing self-regulated learning in responsive open learning environments

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