Multi-Channel Sequence Analysis in Educational Research: An Introduction and Tutorial with R

dc.contributor.authorLópez-Pernas, Sonsoles
dc.contributor.authorSaqr, Mohammed
dc.contributor.authorHelske, Satu
dc.contributor.authorMurphy, Keefe
dc.contributor.organizationfi=sosiologia|en=Sociology|
dc.contributor.organization-code2603303
dc.converis.publication-id459133797
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/459133797
dc.date.accessioned2025-08-28T02:16:48Z
dc.date.available2025-08-28T02:16:48Z
dc.description.abstract<p>This chapter introduces multi-channel sequence analysis, a novel method that examines two or more synchronised sequences. While this approach is relatively new in social sciences, its relevance to educational research is growing as researchers gain access to diverse multimodal temporal data. Throughout this chapter, we describe multi-channel sequence analysis in detail, with an emphasis on how to detect patterns within the sequences, i.e., clusters —or trajectories— of multi-channel sequences that share similar temporal evolutions (or similar trajectories). To illustrate this method we present a step-by-step tutorial in R that analyses students’ sequences of online engagement and academic achievement, exploring their longitudinal association. We cover two approaches for clustering multi-channel sequences: one based on using distance-based algorithms, and the other employing mixture hidden Markov models inspired by recent research.<br></p>
dc.format.pagerange465
dc.format.pagerangeLearning Analytics Methods and Tutorials
dc.identifier.eisbn978-3-031-54464-4
dc.identifier.isbn978-3-031-54463-7
dc.identifier.olddbid208842
dc.identifier.oldhandle10024/191869
dc.identifier.urihttps://www.utupub.fi/handle/11111/34417
dc.identifier.urlhttp://doi.org/10.1007/978-3-031-54464-4_13
dc.identifier.urnURN:NBN:fi-fe2025082792153
dc.language.isoen
dc.okm.affiliatedauthorHelske, Satu
dc.okm.discipline5141 Sociologyen_GB
dc.okm.discipline5141 Sosiologiafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA3 Book
dc.publisherSpringer
dc.publisher.countrySwitzerlanden_GB
dc.publisher.countrySveitsifi_FI
dc.publisher.country-codeCH
dc.publisher.isbn978-81-322;978-3-540;978-3-642;978-3-662;978-3-7908;978-3-8274;978-3-8347;978-90-481;978-94-007;978-94-009;978-94-010;978-94-011;978-94-015;978-94-017;978-94-024;978-0-387;978-0-8176;978-1-4419;978-1-4612;978-1-4613;978-1-4614;978-1-4615;978-1-4684;978-1-4757;978-1-4899;978-1-4939;978-1-5041;978-3-319;978-1-4020;978-0-85729;978-1-4471;978-1-84628;978-1-84800;978-1-84882;978-1-84996;978-1-85233;978-3-211;978-3-7091;978-4-431;978-3-322;978-3-409;978-3-531;978-3-658;978-3-663;978-3-8100;978-981-287;978-981-10;978-981-13;978-3-030;978-981-32;978-981-15;978-981-16;978-981-329;978-981-334;978-981-336;978-3-031;978-981-19;
dc.relation.doi10.1007/978-3-031-54464-4_13
dc.source.identifierhttps://www.utupub.fi/handle/10024/191869
dc.titleMulti-Channel Sequence Analysis in Educational Research: An Introduction and Tutorial with R
dc.title.bookLearning Analytics Methods and Tutorials
dc.year.issued2024

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