A New Era in Multimodal Learning Analytics: Twelve Core Commitments to Ground and Grow MMLA

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (L...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of Learning Analytics Ročník 8; číslo 3; s. 10 - 27
Hlavní autori: Worsley, Marcelo, Martinez-Maldonado, Roberto, D'Angelo, Cynthia
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Society for Learning Analytics Research 01.01.2021
Predmet:
Artificial Intelligence
Data Collection
Data Interpretation
Feedback (Response)
Information Dissemination
Learning Analytics
Learning Experience
Prediction
Research Methodology
Statistical Inference
ISSN:1929-7750, 1929-7750
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12 commitments that we believe are critical for creating effective MMLA innovations. Moreover, as MMLA grows in use, it is important to articulate a set of core commitments that can help guide both MMLA researchers and the broader learning analytics community. The commitments that we describe are deeply rooted in the origins of MMLA and also reflect the ways that MMLA has evolved over the past 10 years. We organize the 12 commitments in terms of (i) data collection, (ii) analysis and inference, and (iii) feedback and data dissemination and argue why these commitments are important for conducting ethical, high-quality MMLA research. Furthermore, in using the language of commitments, we emphasize opportunities for MMLA research to align with established qualitative research methodologies and important concerns from critical studies.
AbstractList Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12 commitments that we believe are critical for creating effective MMLA innovations. Moreover, as MMLA grows in use, it is important to articulate a set of core commitments that can help guide both MMLA researchers and the broader learning analytics community. The commitments that we describe are deeply rooted in the origins of MMLA and also reflect the ways that MMLA has evolved over the past 10 years. We organize the 12 commitments in terms of (i) data collection, (ii) analysis and inference, and (iii) feedback and data dissemination and argue why these commitments are important for conducting ethical, high-quality MMLA research. Furthermore, in using the language of commitments, we emphasize opportunities for MMLA research to align with established qualitative research methodologies and important concerns from critical studies.
Author Martinez-Maldonado, Roberto
Worsley, Marcelo
D'Angelo, Cynthia
Author_xml – sequence: 1
  givenname: Marcelo
  orcidid: 0000-0002-2982-0040
  surname: Worsley
  fullname: Worsley, Marcelo
– sequence: 2
  givenname: Roberto
  orcidid: 0000-0002-8375-1816
  surname: Martinez-Maldonado
  fullname: Martinez-Maldonado, Roberto
– sequence: 3
  givenname: Cynthia
  orcidid: 0000-0001-6998-1052
  surname: D'Angelo
  fullname: D'Angelo, Cynthia
BackLink http://eric.ed.gov/ERICWebPortal/detail?accno=EJ1325255$$DView record in ERIC
BookMark eNp1kEFLw0AQhRdRsNZevQn7BxJ3Z7Pd1FsotSqpXurJwzJJNrIl2chma-m_N7UKIniYmQeP9xi-C3LqOmcIueIs5umUpTebBmNgwGMlpvyEjPgMZpFSkp3-0udk0vcbxpgALsSMjchrRp_Mji48UuvoatsE23YVNjQ36J11bzRz2OyDLftbut6Z5sPQeecPq21taI0LPQ0dXfpu6yqKwwxyR1erPLskZzU2vZl83zF5uVus5_dR_rx8mGd5VArGQ1QJlZZFklR1AcNTaVLCFIsCAKTiqDhArepKgUQEhEQolnKZDoYRqSwEE2Nyfew13pb63dsW_V4vHrkACVIOfnL0S9_1vTe1Lm3AYDsXPNpGc6a_GOqBoT4w1AeGQyz-E_up_ifwCWDEcrQ
CitedBy_id crossref_primary_10_1109_TLT_2023_3246507
crossref_primary_10_1016_j_eswa_2025_128948
crossref_primary_10_1111_bjet_13498
crossref_primary_10_17853_1994_5639_2025_7_33_71
crossref_primary_10_1080_1743727X_2024_2410306
crossref_primary_10_1007_s10758_025_09868_0
crossref_primary_10_3233_IDT_230727
crossref_primary_10_1016_j_caeai_2025_100426
crossref_primary_10_1080_01587919_2022_2064824
crossref_primary_10_1080_10447318_2023_2181878
crossref_primary_10_1109_ACCESS_2024_3493621
crossref_primary_10_3389_feduc_2024_1356537
crossref_primary_10_1109_ACCESS_2025_3572467
crossref_primary_10_3390_s22218556
crossref_primary_10_3389_feduc_2023_1220688
crossref_primary_10_1111_bjet_13391
crossref_primary_10_1111_bjet_13320
crossref_primary_10_1016_j_actpsy_2024_104389
crossref_primary_10_1145_3622784
crossref_primary_10_1016_j_chb_2022_107304
crossref_primary_10_1016_j_compedu_2023_104784
crossref_primary_10_3389_feduc_2022_840947
crossref_primary_10_3389_fpsyg_2023_1103311
ContentType Journal Article
DBID AAYXX
CITATION
ERI
GA5
DOI 10.18608/jla.2021.7361
DatabaseName CrossRef
ERIC
ERIC - Full Text Only (Discovery)
DatabaseTitle CrossRef
ERIC
DatabaseTitleList CrossRef
ERIC
DeliveryMethod fulltext_linktorsrc
EISSN 1929-7750
ERIC EJ1325255
EndPage 27
ExternalDocumentID EJ1325255
10_18608_jla_2021_7361
GroupedDBID AAYXX
ABOPQ
ALMA_UNASSIGNED_HOLDINGS
CITATION
FRS
M~E
OK1
ERI
GA5
ID FETCH-LOGICAL-c301t-d378cb44dfb233984c26abb222571a7122f7fd725aa2a243708158a71e385b303
ISICitedReferencesCount 35
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000741448300002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1929-7750
IngestDate Tue Dec 02 16:28:00 EST 2025
Sat Nov 29 02:59:07 EST 2025
Tue Nov 18 20:20:12 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c301t-d378cb44dfb233984c26abb222571a7122f7fd725aa2a243708158a71e385b303
ORCID 0000-0001-6998-1052
0000-0002-2982-0040
0000-0002-8375-1816
OpenAccessLink http://eric.ed.gov/ERICWebPortal/detail?accno=EJ1325255
PageCount 18
ParticipantIDs eric_primary_EJ1325255
crossref_citationtrail_10_18608_jla_2021_7361
crossref_primary_10_18608_jla_2021_7361
PublicationCentury 2000
PublicationDate 2021-01-01
PublicationDateYYYYMMDD 2021-01-01
PublicationDate_xml – month: 01
  year: 2021
  text: 2021-01-01
  day: 01
PublicationDecade 2020
PublicationTitle Journal of Learning Analytics
PublicationYear 2021
Publisher Society for Learning Analytics Research
Publisher_xml – name: Society for Learning Analytics Research
SSID ssj0003213390
Score 2.3781614
Snippet Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics...
SourceID eric
crossref
SourceType Open Access Repository
Enrichment Source
Index Database
StartPage 10
SubjectTerms Artificial Intelligence
Data Collection
Data Interpretation
Feedback (Response)
Information Dissemination
Learning Analytics
Learning Experience
Prediction
Research Methodology
Statistical Inference
Title A New Era in Multimodal Learning Analytics: Twelve Core Commitments to Ground and Grow MMLA
URI http://eric.ed.gov/ERICWebPortal/detail?accno=EJ1325255
Volume 8
WOSCitedRecordID wos000741448300002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 1929-7750
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0003213390
  issn: 1929-7750
  databaseCode: M~E
  dateStart: 20140101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Bb9MwFLZK4cAFDcHEYCAfQBxQhmI7scMt2ooQIhOHIU3iEDmJI4rSZCpZOzjwT_ivey9OnZRt0jhwsSzXttK8L_bzp_c-E_JS5yw0wkjPRKX2RFAGnjZMegGXRR5mjAtWdpdNyONjdXoafZ5M_mxyYVaVrGt1cRGd_VdTQxsYG1Nn_8HcblJogDoYHUowO5S3MnzcxSzOlhqpjC6_dtEUSFc7EgR1SFCduaPW16Za4dV1SywWi3lrc97AJUVayiq5YnX9Jkk-xTf4slfndot942jxBNMqq2bgwFHAwPzyEl0VcB4omiHS23U6esVkjHG3ltH9Wbff5nrMVDB_xFTYxRVcMfDmrdDsgbmmrV-R1Qh4fLS69gGwdp-2kgJXdgAVdmkN3ysUlWL-geRW7H1bavuvLdAFJuKRCGdIYXyK41Mcf4fcZTKIcNFMfg8UHmdwwO9YPPcvellQnOLt1iNsuT3TTThc78ac7JAHvc1obHHzkExM_Yh8jSlghgJm6LymA2boxq7U2fUdtYihiBg6QgxtG2oRQwExWF1TRMxj8uX97OTwg9ffuuHlsNi3XsGlyjMhihK-VB4pAV-zzjLkBaSvpc9YKctCskBrplHOEpzKQMEPhqsgA49ol0zrpjZPCA2Nz4zv5-AGKmFCnhVRloFHyZUWItTlHvE2LyXNe0l6vBmlSq-3wx557fqfWTGWG3vu4jt2vWYffc4COD4_vfUUz8j9AcT7ZNouz81zci9ftfMfyxcdEi4B2lqFYQ
linkProvider ISSN International Centre
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+New+Era+in+Multimodal+Learning+Analytics%3A+Twelve+Core+Commitments+to+Ground+and+Grow+MMLA&rft.jtitle=Journal+of+Learning+Analytics&rft.au=Worsley%2C+Marcelo&rft.au=Martinez-Maldonado%2C+Roberto&rft.au=D%27Angelo%2C+Cynthia&rft.date=2021-01-01&rft.issn=1929-7750&rft.eissn=1929-7750&rft.volume=8&rft.issue=3&rft.spage=10&rft.epage=27&rft_id=info:doi/10.18608%2Fjla.2021.7361&rft.externalDBID=n%2Fa&rft.externalDocID=10_18608_jla_2021_7361
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1929-7750&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1929-7750&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1929-7750&client=summon