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MMALA: Developing and Evaluating a Maturity Model for Adopting Learning Analytics

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Title: MMALA: Developing and Evaluating a Maturity Model for Adopting Learning Analytics
Language: English
Authors: Elyda Freitas (ORCID 0000-0001-7439-9040), Fernando Fonseca (ORCID 0000-0001-5303-6937), Vinicius Cardoso Garcia (ORCID 0000-0001-6904-7470), Taciana Pontual Falcao (ORCID 0000-0003-2775-4913), Elaine Marques (ORCID 0000-0002-5991-1672), Dragan Gaševic (ORCID 0000-0001-9265-1908), Rafael Ferreira Mello (ORCID 0000-0003-3548-9670)
Source: Journal of Learning Analytics. 2024 11(1):67-86.
Availability: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
Peer Reviewed: Y
Page Count: 20
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Learning Analytics, Higher Education, Models, Program Implementation, Evaluation, Foreign Countries
Geographic Terms: Brazil
ISSN: 1929-7750
Abstract: Learning analytics (LA) adoption is a challenging task for higher education institutions (HEIs) since it involves different aspects of the academic environment, such as information technology infrastructure, human resource management, ethics, and pedagogical issues. Therefore, it is necessary to provide institutions with supporting instruments to deal with these challenges. Although there has been much research on factors that are associated with the adoption of LA in HEIs, there has been much less research on specific models that can be used to guide actual adoption. In this sense, we developed MMALA, a Maturity Model for Adopting Learning Analytics. It is a guide that describes the necessary practices for taking the first steps in this area and enables institutions to reach higher levels of maturity in LA use, culminating in an organized and systematic adoption. In this paper, we describe the development process of MMALA, focusing on the model evaluation, which used both the questionnaire and the expert opinion method. MMALA can also give institutions an overview of their current situation regarding LA adoption. In this sense, we present the results of the maturity evaluation of three Brazilian HEIs using MMALA.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1423448
Database: ERIC
FullText Text:
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  Data: MMALA: Developing and Evaluating a Maturity Model for Adopting Learning Analytics
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  Data: <searchLink fieldCode="AR" term="%22Elyda+Freitas%22">Elyda Freitas</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7439-9040">0000-0001-7439-9040</externalLink>)<br /><searchLink fieldCode="AR" term="%22Fernando+Fonseca%22">Fernando Fonseca</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5303-6937">0000-0001-5303-6937</externalLink>)<br /><searchLink fieldCode="AR" term="%22Vinicius+Cardoso+Garcia%22">Vinicius Cardoso Garcia</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6904-7470">0000-0001-6904-7470</externalLink>)<br /><searchLink fieldCode="AR" term="%22Taciana+Pontual+Falcao%22">Taciana Pontual Falcao</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2775-4913">0000-0003-2775-4913</externalLink>)<br /><searchLink fieldCode="AR" term="%22Elaine+Marques%22">Elaine Marques</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-5991-1672">0000-0002-5991-1672</externalLink>)<br /><searchLink fieldCode="AR" term="%22Dragan+Gaševic%22">Dragan Gaševic</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-9265-1908">0000-0001-9265-1908</externalLink>)<br /><searchLink fieldCode="AR" term="%22Rafael+Ferreira+Mello%22">Rafael Ferreira Mello</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3548-9670">0000-0003-3548-9670</externalLink>)
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  Data: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
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  Data: 20
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Learning+Analytics%22">Learning Analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Models%22">Models</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Implementation%22">Program Implementation</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation%22">Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Brazil%22">Brazil</searchLink>
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  Data: 1929-7750
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  Data: Learning analytics (LA) adoption is a challenging task for higher education institutions (HEIs) since it involves different aspects of the academic environment, such as information technology infrastructure, human resource management, ethics, and pedagogical issues. Therefore, it is necessary to provide institutions with supporting instruments to deal with these challenges. Although there has been much research on factors that are associated with the adoption of LA in HEIs, there has been much less research on specific models that can be used to guide actual adoption. In this sense, we developed MMALA, a Maturity Model for Adopting Learning Analytics. It is a guide that describes the necessary practices for taking the first steps in this area and enables institutions to reach higher levels of maturity in LA use, culminating in an organized and systematic adoption. In this paper, we describe the development process of MMALA, focusing on the model evaluation, which used both the questionnaire and the expert opinion method. MMALA can also give institutions an overview of their current situation regarding LA adoption. In this sense, we present the results of the maturity evaluation of three Brazilian HEIs using MMALA.
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  Data: 2024
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  Data: EJ1423448
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      – Text: English
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      – SubjectFull: Learning Analytics
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      – SubjectFull: Higher Education
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      – SubjectFull: Models
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