Learning Analytics on Bodong Chen

Network Motifs as Codes

Tue, 07 Jun 2022 00:00:00 +0000

I’ve been working on a framework of applying socio-semantic network analysis to discourse data.

Socio-semantic networks are two-mode, dual-layer networks that are made of actors (e.g., learners), semantic entities (e.g., words), and their relations. Socio-semantic network analysis brings together the study of relations among actors (human networks), relations among semantic elements (semantic networks), and relations among these two orders of networks (Basov et al., 2020). Such a dual-layer network analysis approach is not only useful for examining the duality of socio-semantic relations, it also applies to other settings such as socio-ecological analysis that’s interested in the interactions between social structures and ecological resources (Bodin & Tengö, 2012).

Learning Analytics for Understanding and Supporting Collaboration

Mon, 21 Mar 2022 00:00:00 +0000

Abstract

Collaboration is an important competency in the modern society. To harness the intersection of learning, work, and collaboration with analytics, several fundamental challenges need to be addressed. This chapter about collaboration analytics aims to highlight these challenges for the learning analytics community. We first survey the conceptual landscape of collaboration and learning with a focus on the computer-supported collaborative learning (CSCL) literature while attending to perspectives from computer supported cooperative work (CSCW). Grounded in the conceptual exploration, we then distinguish two salient strands of collaboration analytics: (a) computational analysis of collaboration that applies computational methods to examining collaborative processes; and (b) analytics for collaboration which is primarily concerned with designing and deploying data analytics in authentic contexts to facilitate collaboration. Examples and cases representing different contexts for learning and analytical frames are presented, followed by a discussion of key challenges and future directions.

Socio-Semantic Network Motifs Framework for Discourse Analysis

Sun, 13 Mar 2022 00:00:00 +0000

ABSTRACT

Effective collaborative discourse requires both cognitive and social engagement of students. To investigate complex socio-cognitive dynamics in collaborative discourse, this paper proposes to model collaborative discourse as a socio-semantic network (SSN) and then use network motifs – defined as recurring, significant subgraphs – to characterize the network and hence the discourse. To demonstrate the utility of our SSN motifs framework, we applied it to a sample dataset. While more work needs to be done, the SSN motifs framework shows promise as a novel, theoretically informed approach to discourse analysis.

Socio-Temporal Dynamics in Peer Interaction Events

Fri, 24 Jan 2020 12:19:31 -0600

A Call for Third-Order Change in Learning Analytics

Thu, 06 Jun 2019 12:28:46 -0500

[Disclaimer: It’s summer time, meaning time for some bold statements.]

“Any educational intervention, for the obvious, common-sense reasons mentioned above, can do harm… ignoring side effects is one of the main reasons for the perpetual wars and pendulum swings in education.” — Yong Zhao (2018)

Education often turns to other disciplines for inspirations. In medicine, precision medicine “takes into account individual variability in genes, environment, and lifestyle for each person” when treating diseases. In business, business intelligence harnesses information and analytics to improve and optimize decisions and performance. All good stuff, right?

Towards Value-Sensitive Learning Analytics Design

Mon, 04 Mar 2019 21:08:26 -0600

Towards Value-Sensitive Learning Analytics Design

Fri, 01 Mar 2019 00:00:00 +0000

Technology Use in K-12 Schools: Cases from North America

Thu, 08 Nov 2018 00:00:00 +0000

Fostering student engagement in online discussion through social learning analytics

Thu, 25 Jan 2018 00:00:00 +0000

A biased introduction to Learning Analytics: Kicking-off #UMNLACoP

Thu, 23 Mar 2017 00:00:00 +0000

Today, we kicked off our Learning Analytics Community of Practice at UMN (#UMNLACoP)! Launching this CoP has been a joint effort among the Center for Educational Innovation, the College of Liberal Arts, the Libraries, and the College of Education and Human Development.

During today’s kick-off event, I spent 15 minutes presenting a quick introduction to the field of Learning Analytics. Below is an audio recording of my presentation.