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The Role of Learning Motivation Factors in Deepseek Generative AI Adoption among Higher Education Students in India

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Title: The Role of Learning Motivation Factors in Deepseek Generative AI Adoption among Higher Education Students in India
Language: English
Authors: Ravi Sankar Pasupuleti, Deevena Charitha Jangam, Anitha Bhimavarapu, Venkata Reddy Gunnam, Venkata Ramana Sikhakolli, Deepthi Thiyyagura
Source: Electronic Journal of e-Learning. 2025 23(4):1-14.
Availability: Academic Conferences Limited. Curtis Farm, Kidmore End, Nr Reading, RG4 9AY, UK. Tel: +44-1189-724148; Fax: +44-1189-724691; e-mail: info@academic-conferences.org; Web site: https://academic-publishing.org/index.php/ejel/index
Peer Reviewed: Y
Page Count: 14
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, College Students, Learning Motivation, Educational Technology, Self Efficacy, Goal Orientation, Usability, Intention
Geographic Terms: India
ISSN: 1479-4403
Abstract: This research explores adoption of the Deepseek, an artificial intelligence (AI) platform among higher education students in India by integrating the Technology Acceptance Model (TAM) with learning motivation factors. Given the rapid rise of AI-based platforms in educational sector, understanding their adoption is not only timely but also essential for ensuring equitable and effective learning outcomes. Addressing a critical research gap in understanding of rapidly evolving EdTech sector, the research blends constructs such as learning interest, achievement goals, self-efficacy, and subjective norms in expanding the typical TAM model. This integrative approach allows for a more holistic framework that captures both technological perceptions and learner-driven motivational factors, making the model especially relevant in emerging economies where educational technology adoption varies widely. Data were gathered using an online survey via Google Forms, providing 346 valid responses from students. The sample consisted of students from diverse academic disciplines, ensures representativeness across different fields of study and thereby enhancing the generalizability of the results. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS-3 software. The findings support the extended TAM model which indicated that learning interest and achievement goals have significant impact on perceived ease of use. Self-efficacy and subjective norms have significant impact on perceived usefulness and behavioral intention has significant impact on actual usage, demonstrating its pivotal role in technology adoption. These relationships suggest that motivation-related constructs are not peripheral but central in shaping how students interact with AI-powered platforms. This study advances the literature on educational technology by establishing a new TAM model as applied to AI-powered learning tools in emerging economies. The practical implications are that developers of Deepseek need to make the platform more user-centered in order to increase adoption. Future research avenues involve analyzing other contextual factors and longitudinal patterns of adoption over time. These findings provide useful insights for stakeholders who want to maximize AI learning tool integration in universities.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1489017
Database: ERIC
FullText Links:
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  Data: The Role of Learning Motivation Factors in Deepseek Generative AI Adoption among Higher Education Students in India
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Motivation%22">Learning Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Goal+Orientation%22">Goal Orientation</searchLink><br /><searchLink fieldCode="DE" term="%22Usability%22">Usability</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink>
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  Data: 1479-4403
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This research explores adoption of the Deepseek, an artificial intelligence (AI) platform among higher education students in India by integrating the Technology Acceptance Model (TAM) with learning motivation factors. Given the rapid rise of AI-based platforms in educational sector, understanding their adoption is not only timely but also essential for ensuring equitable and effective learning outcomes. Addressing a critical research gap in understanding of rapidly evolving EdTech sector, the research blends constructs such as learning interest, achievement goals, self-efficacy, and subjective norms in expanding the typical TAM model. This integrative approach allows for a more holistic framework that captures both technological perceptions and learner-driven motivational factors, making the model especially relevant in emerging economies where educational technology adoption varies widely. Data were gathered using an online survey via Google Forms, providing 346 valid responses from students. The sample consisted of students from diverse academic disciplines, ensures representativeness across different fields of study and thereby enhancing the generalizability of the results. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS-3 software. The findings support the extended TAM model which indicated that learning interest and achievement goals have significant impact on perceived ease of use. Self-efficacy and subjective norms have significant impact on perceived usefulness and behavioral intention has significant impact on actual usage, demonstrating its pivotal role in technology adoption. These relationships suggest that motivation-related constructs are not peripheral but central in shaping how students interact with AI-powered platforms. This study advances the literature on educational technology by establishing a new TAM model as applied to AI-powered learning tools in emerging economies. The practical implications are that developers of Deepseek need to make the platform more user-centered in order to increase adoption. Future research avenues involve analyzing other contextual factors and longitudinal patterns of adoption over time. These findings provide useful insights for stakeholders who want to maximize AI learning tool integration in universities.
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  Data: 2025
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  Data: EJ1489017
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 1
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Learning Motivation
        Type: general
      – SubjectFull: Educational Technology
        Type: general
      – SubjectFull: Self Efficacy
        Type: general
      – SubjectFull: Goal Orientation
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      – SubjectFull: Usability
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      – SubjectFull: Intention
        Type: general
      – SubjectFull: India
        Type: general
    Titles:
      – TitleFull: The Role of Learning Motivation Factors in Deepseek Generative AI Adoption among Higher Education Students in India
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            NameFull: Venkata Reddy Gunnam
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            NameFull: Venkata Ramana Sikhakolli
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