Analysing behavioural sequences of online learners : lag sequential analysis using GSEQ /

This dataset is designed for teaching lag sequential analysis (LSA). By identifying time-serial data of sequential behaviours, researchers locate the dependency among users' activity sequences. This online learner behaviour dataset stores a college-level course activity that was fully online-ta...

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Bibliographic Details
Main Authors:	Li, Shao-Chi, active 2022 (Author), Chen, Ken-Zen (Author)
Format:	eBook
Language:	English
Published:	London : SAGE Publications, Ltd., 2022.
Subjects:	Behavioral assessment > Databases. Web-based instruction > Databases. Data sets. Jeux de données. Behavioral assessment Data sets Web-based instruction Databases
Online Access:	Connect to the full text of this electronic book

Description
Summary:	This dataset is designed for teaching lag sequential analysis (LSA). By identifying time-serial data of sequential behaviours, researchers locate the dependency among users' activity sequences. This online learner behaviour dataset stores a college-level course activity that was fully online-taught on a Moodle (a learning management system). This example demonstrates the ideas and working steps in conducting LSA, and how educational researchers portray and compare the online learning patterns. This guide includes the datasets, the main idea behind LSA, how to use Generalised Sequential Querier (GSEQ) to conduct LSA, and how to report and visualise the result in the Student Guide and How-to Guide for GESQ.
Physical Description:	1 online resource : illustrations
ISBN:	9781529607918 1529607914