IDEAS home Printed from https://ideas.repec.org/a/ibn/jsd123/v14y2024i2p96.html

Opportunities for Adaptive Learning Environments to Promote Sustainability-Oriented Innovation Competence in Vocational Education and Training

Author

Listed:
  • Florian Berding
  • Andreas Slopinski
  • Regina Frerichs
  • Karin Rebmann

Abstract

Achieving a sustainable economic system is a key challenge facing society. However, sustainable business to date has been only minimally considered when it comes to the requisites and curricula of business trainees. It generally has been left up to schools and teachers to provide their students with sustainable business skills. This involves creating teaching and training that effectively harmonize with learner requirements. To support teachers in this process, the following develops a sustainability-oriented innovation competence typology using a latent profile analysis based on data gathered from 1,149 business trainees who were in the first, second, or third year of their apprenticeship. This typology can be used to plan and develop classroom teaching. Competency assessment was done using a multiple-choice test along with a questionnaire to determine students’ beliefs about sustainable development. The latent profile analysis revealed six groups of learner competence profiles, each of which require specific teaching when it comes to achieving sustainable innovation skills. Based on these, the following paper develops recommendations for specific teaching methods and lessons that effectively promote business trainee sustainability-oriented innovation competence, while at the same time including their specific requirements into teaching.

Suggested Citation

  • Florian Berding & Andreas Slopinski & Regina Frerichs & Karin Rebmann, 2024. "Opportunities for Adaptive Learning Environments to Promote Sustainability-Oriented Innovation Competence in Vocational Education and Training," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 14(2), pages 1-96, July.
    • Handle: RePEc:ibn:jsd123:v:14:y:2024:i:2:p:96
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/jsd/article/download/0/0/44869/47467
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/jsd/article/view/0/44869
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gilles Celeux & Gilda Soromenho, 1996. "An entropy criterion for assessing the number of clusters in a mixture model," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 195-212, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shouchuang Zhang & Ting Wang & Lanyue Zhang & Yuehui Wei & Weiyan Jian & Jing Guo, 2024. "Relationship between social inequality perception patterns and depressive symptoms among Chinese adults: A national representative longitudinal study," International Journal of Social Psychiatry, , vol. 70(5), pages 933-944, August.
    2. Scrucca, Luca, 2016. "Identifying connected components in Gaussian finite mixture models for clustering," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 5-17.
    3. Marianna Virtanen & Jussi Vahtera & Jenny Head & Rosemary Dray-Spira & Annaleena Okuloff & Adam G Tabak & Marcel Goldberg & Jenni Ervasti & Markus Jokela & Archana Singh-Manoux & Jaana Pentti & Marie , 2015. "Work Disability among Employees with Diabetes: Latent Class Analysis of Risk Factors in Three Prospective Cohort Studies," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    4. Soojeong Jeong & Kaylee Litson & Jennifer Blaney & David F. Feldon, 2020. "Shifting Gears: Characteristics and Consequences of Latent Class Transitions in Doctoral Socialization," Research in Higher Education, Springer;Association for Institutional Research, vol. 61(8), pages 1027-1053, December.
    5. Mari Huhtala & Muel Kaptein & Joona Muotka & Taru Feldt, 2022. "Longitudinal Patterns of Ethical Organisational Culture as a Context for Leaders’ Well-Being: Cumulative Effects Over 6 Years," Journal of Business Ethics, Springer, vol. 177(2), pages 421-442, May.
    6. Ayşegül Karaca-Atik & Marjan J. Gorgievski & Marieke Meeuwisse & Guus Smeets, 2024. "Possessing 21st-Century Skills and Building Sustainable Careers: Early-Career Social Sciences Graduates’ Perspectives," Sustainability, MDPI, vol. 16(8), pages 1-21, April.
    7. Julian Aichholzer & Sylvia Kritzinger & Carolina Plescia, 2021. "National identity profiles and support for the European Union," European Union Politics, , vol. 22(2), pages 293-315, June.
    8. Xiongya Li & Xiuqin Bai & Weixing Song, 2025. "Robust mixture of linear mixed modeling via multivariate Laplace distribution," Computational Statistics, Springer, vol. 40(8), pages 4209-4230, November.
    9. Christian Schellhase & Göran Kauermann, 2012. "Density estimation and comparison with a penalized mixture approach," Computational Statistics, Springer, vol. 27(4), pages 757-777, December.
    10. Fadong Chen & Urs Fischbacher, 2015. "Cognitive Processes of Distributional Preferences: A Response Time Study," TWI Research Paper Series 101, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    11. Adrian Bruhin & Ernst Fehr & Daniel Schunk, 2019. "The many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 1025-1069.
    12. Nicoleta Serban & Huijing Jiang, 2012. "Multilevel Functional Clustering Analysis," Biometrics, The International Biometric Society, vol. 68(3), pages 805-814, September.
    13. Jacky C. K. Ng & Joanne Y. H. Chong & Hilary K. Y. Ng, 2023. "The way I see the world, the way I envy others: a person-centered investigation of worldviews and the malicious and benign forms of envy among adolescents and adults," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    14. Danks, Nicholas P. & Sharma, Pratyush N. & Sarstedt, Marko, 2020. "Model selection uncertainty and multimodel inference in partial least squares structural equation modeling (PLS-SEM)," Journal of Business Research, Elsevier, vol. 113(C), pages 13-24.
    15. Gillian C. Williams & Karen A. Patte & Mark A. Ferro & Scott T. Leatherdale, 2021. "Associations between Longitudinal Patterns of Substance Use and Anxiety and Depression Symptoms among a Sample of Canadian Secondary School Students," IJERPH, MDPI, vol. 18(19), pages 1-14, October.
    16. Kim, Daeyoung & Seo, Byungtae, 2014. "Assessment of the number of components in Gaussian mixture models in the presence of multiple local maximizers," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 100-120.
    17. Eun Young Choi & Seung-Hye Choi & Haeyoung Lee, 2021. "The Association between Job Quality Profiles and Work-Life Balance among Female Employees in Korea: A Latent Profile Analysis," IJERPH, MDPI, vol. 18(4), pages 1-12, February.
    18. Jeffrey H Dorfman & Christian Gregory & Zhongyuan Liu & Ran Huo, 2019. "Re‐Examining the SNAP Benefit Cycle Allowing for Heterogeneity," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(3), pages 404-433, September.
    19. Mélissa Lemoine & Gerhard Gmel & Simon Foster & Simon Marmet & Joseph Studer, 2020. "Multiple trajectories of alcohol use and the development of alcohol use disorder: Do Swiss men mature-out of problematic alcohol use during emerging adulthood?," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    20. Sarstedt, Marko & Salcher, André, 2007. "Modellselektion in Finite Mixture PLS-Modellen," Discussion Papers in Business Administration 1394, University of Munich, Munich School of Management.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:jsd123:v:14:y:2024:i:2:p:96. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.