MONITORING AND ANALYSIS OF LEARNING INTERACTIONS IN DIGITAL LEARNING ECOSYSTEMS

Maka Eradze, Tbilisi State University/Tallinn University (Supervisor Peeter Normak)

Structure Context and Background

Personal perspective and choice of topic Main Concepts and Contextual inquiry

Learning interactions Digital learning ecosystems Dippler Learning analytics

Theoretical perspective Communities of inquiry Activity Base Scheme – Tin Can Api and Learning Activity

stream of Dippler Methodological approach

Design-based research

Personal perspective Worked as an elearning coordinator for 3.5 years in Tbilisi State University At the same time enrolled in the PhD program Have created a strategic development plan for TSU Have made a student reported survey on TEL practices The “team” consisted of two people – myself and an IT person Have developed Moodle based elearning courses Main characteristics of the Georgian TEL paradigm (to name a few)

Closed LMS based system – no readiness to open up (questions like:” will others copy our courses”)

No academic freedom and autonomy, no incentives for the development of new pedagogical scenarios

Little self-directed learning Little flexibility

Cooperation with different partners, amongst them Estonian cooperation was the most successful

Course example

Context and background - interaction

Defining interaction “reciprocal events that require at least two

objects and two actions. Interactions occur when these objects and events mutually influence each other” (Wagner, 1994)

Moore’s theory of transactional distance (1993)

Holmbergs (1989) Guided didactic discussion

Context and background – interaction theories Moore’s three types of interaction (1989) Holmberg’s notion of internal didactic conversation Interaction equivalency theorem (Anderson 2005) Thesis 1

Deep and meaningful formal learning is supported as long as one of the three forms of interaction (student-teacher. Student-student, student-content) is at high level. The other two may be offered at minimal levels, or even eliminated, without degrading the educational experience.

Thesis 2. High levels of more than one of these three modes will likely provide a more satisfying educational expeirence, altough these expeirences may not be as cost-or time-effective as less interactive learning sequences.

Later Anderson introduced other 2 additional Theses: Thesis 3. Deep and meaningful formal Teaching is supported as long as one of the three forms of

interaction (Teacher-student. Teacher-content, teacher-teacher) is at a high level. The other tow may be offered at minimal level, or even eliminated, without degrading the educational experience

Thesis 4. Deep and meaningful formal Teaching and learning is supported as long as one of the three forms of interaction (student-content. Teacher-content, content-content) is at a high level. The other tow may be offered at minimal level, or even eliminated, without degrading the educational experience

For Anderson – the last two theses demand a shift from student centered to teacher and content centered. This regarded as a personification of the content and is consistent with the Anderson theory to add three more types of interaction and increasing capacity of “smart” content.

Context and background - DLE LMS and DLE DLE - “an adaptive socio-technical system

consisting of mutually interacting digital species (tools, services, content used in learning process) and communities of users (learners, facilitators, experts) together with their social, economical and cultural environment.(Laanpere et al 2012)

DLE replaces the traditional learning management systems

In an LMS interactions take place in a closed system and is kept in a centralized database

DLE is a distributed set of online tools and services

Context and background - Dippler A prototype - Digital Learning Ecosystem Three interconnected components:

Central learning flow management service, Institutional course management environment Personal blog-based e-portfolio for each

learner. Learners integrate external social media tools,

services and content to their e-portfolios through simple technologies as RSS-feeds, embedding, linking and widgets

Context and background – learning analytics

According to the 1st International Conference on Learning Analytics and Knowledge, “learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.” (http://www.educause.edu/ero/article/learning-analytics-new-black)

learning analytics takes the Big Data and tries to make sense out of this data

Theoretical framework – Communities of inquiry Social Presence

Effective communication Open communication Group cohesion

Cognitive presence Exploration Construction Resolution Confirmation of understanding

Teaching Presence Design Facilitate Direct instruction

Research questions

In order to add learning analytics functionalities to DLE like Dippler, there are two necessary steps to be taken: harvesting, storing and monitoring

interaction-related data with rich semantics and

identifying methods and tools for analyzing and visualizing the data.

Research questions My initial question:

how the interactions happen in DLE? And how can we measure depth/quality of the

interactions and their relation to learning?That lead to the questions of: How to make it possible to analyze interactions in

DLE? Ways of monitoring? Ways of analysis? Could there be other theoretical frameworks based

on which we could analyze the data?

Activity streams – a new type of learning interaction analytics Activity Base Schema (Facebook example) Dippler Activity streams Tin Can api

Comes from ADL (advanced distributed learning) Is a recent development (version 0.95) No much research on it Records learning experiences as statements consisting

<Actor (learner)> <verb> <object>, with <result>, in <context>

The question is how to expand the dippler activity streams to contain the learning vocabulary having all the existing experiences in mind?

The suggested view of LIA – Learning Interaction Analytics – 4 levels By definition: Social network analysis [SNA] is the

mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities (http://www.orgnet.com/sna.html) It measures based on the location of the figure in the network.

Learning Analytics goes beyond the mappings and relationship measuring and analyzes frequencies and tries to analyze giving the data semantics after the interactions take place

Adding Semantics to the analytics Analyze depth/quality of interactions

Methodological approach: Design based research

Design-based research makes it possible to design and evaluate the innovation process

Iterative Modeling Prototyping Validating