{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T21:36:43Z","timestamp":1779917803709,"version":"3.53.1"},"reference-count":37,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T00:00:00Z","timestamp":1751414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In this article, we present a hybrid optimization methodology using the whale optimization algorithm and Markov Chain Monte Carlo sampling technique in a teachers\u2019 training development program regarding creativity in technology-enhanced learning design. Finding the best possible training for creativity in learning design with technology is a complex task, as many dynamic and multi-model variables need to be taken into consideration. When designing the best possible training, the whale optimization algorithm helped us in determining the right methods, resources, content, and assessment. A further Markov Chain Monte Carlo-based approach helped us in deciding with accuracy that these were the correct parameters of our training. In this article, we show that metaheuristic algorithms like the whale optimization algorithm, validated by a Markov chain technique like Markov Chain Monte Carlo, can help not only in areas like machine learning but also in fields without structured data, like creativity in technology-enhanced learning design. The best possible training for a teacher\u2019s professional development in creative learning design is collaborative, hands-on, and utilizes creativity definitions for the product along with technology integration learning design models.<\/jats:p>","DOI":"10.3390\/a18070407","type":"journal-article","created":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T04:11:04Z","timestamp":1751429464000},"page":"407","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["The Whale Optimization Algorithm and Markov Chain Monte Carlo-Based Approach for Optimizing Teacher Professional Development in Creative Learning Design with Technology"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8594-7483","authenticated-orcid":false,"given":"Kalliopi","family":"Rigopouli","sequence":"first","affiliation":[{"name":"Business Administration Department, University of West Attica, 250 Thivon & Petrou Ralli Str., Egaleo, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6656-260X","authenticated-orcid":false,"given":"Dimitrios","family":"Kotsifakos","sequence":"additional","affiliation":[{"name":"Business Administration Department, University of West Attica, 250 Thivon & Petrou Ralli Str., Egaleo, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8420-8663","authenticated-orcid":false,"given":"Yannis","family":"Psaromiligkos","sequence":"additional","affiliation":[{"name":"Business Administration Department, University of West Attica, 250 Thivon & Petrou Ralli Str., Egaleo, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Rigopouli, K., Kotsifakos, D., and Psaromiligkos, Y. 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