{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T12:55:35Z","timestamp":1769259335187,"version":"3.49.0"},"reference-count":35,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T00:00:00Z","timestamp":1768953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007228","name":"Universidad Aut\u00f3noma de Baja California","doi-asserted-by":"publisher","award":["402\/6\/C\/53\/25"],"award-info":[{"award-number":["402\/6\/C\/53\/25"]}],"id":[{"id":"10.13039\/501100007228","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012725","name":"TECNM","doi-asserted-by":"crossref","award":["TIJU-PYR-2025-22735"],"award-info":[{"award-number":["TIJU-PYR-2025-22735"]}],"id":[{"id":"10.13039\/100012725","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100012725","name":"TECNM","doi-asserted-by":"crossref","award":["18820.23-P"],"award-info":[{"award-number":["18820.23-P"]}],"id":[{"id":"10.13039\/100012725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Integrating people with hearing disabilities into schools is one of the biggest problems that Latin American societies face. Mexican Sign Language (MSL) is the main language and culture of the deaf community in Mexico. However, its use in formal education is still limited by structural inequalities, a lack of qualified interpreters, and a lack of technology that can support personalized instruction. This study outlines the conceptualization and development of a mobile application designed as an adaptive assistive technology for learning MSL, utilizing a combination of computer vision techniques, deep learning algorithms, and personalized pedagogical interaction. The suggested system uses convolutional neural networks (CNNs) and pose-estimation models to recognize hand gestures in real time with 95.7% accuracy. It then gives the learner instant feedback by changing the difficulty level. A dynamic learning engine automatically changes the level of difficulty based on how well the learner is doing, which helps them learn signs and phrases over time. The Scrum agile methodology was used during the development process. This meant that educators, linguists, and members of the deaf community all worked together to design the product. Early tests show that sign recognition accuracy and indicators of user engagement and motivation show favorable performance and are at appropriate levels. This proposal aims to enhance inclusive digital ecosystems and foster linguistic equity in Mexican education through scalable, mobile, and culturally relevant technologies, in addition to its technical contributions.<\/jats:p>","DOI":"10.3390\/fi18010061","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T13:59:54Z","timestamp":1769003994000},"page":"61","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Assistive Technologies for Learning Mexican Sign Language: Design of a Mobile Application with Computer Vision and Personalized Educational Interaction"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9913-592X","authenticated-orcid":false,"given":"Carlos","family":"Hurtado-S\u00e1nchez","sequence":"first","affiliation":[{"name":"Ciencias Econ\u00f3mico Administrativas, Instituto Tecnol\u00f3gico de Tijuana, Tecnol\u00f3gico Nacional de M\u00e9xico, Tijuana 22414, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0266-2951","authenticated-orcid":false,"given":"Ricardo Rosales","family":"Cisneros","sequence":"additional","affiliation":[{"name":"Ciencias Econ\u00f3mico Administrativas, Instituto Tecnol\u00f3gico de Tijuana, Tecnol\u00f3gico Nacional de M\u00e9xico, Tijuana 22414, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5437-8215","authenticated-orcid":false,"given":"Jos\u00e9 Ricardo","family":"C\u00e1rdenas-Valdez","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda El\u00e9ctrica y Electr\u00f3nica, Instituto Tecnol\u00f3gico de Tijuana, Tecnol\u00f3gico Nacional de M\u00e9xico, Tijuana 22414, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3721-5630","authenticated-orcid":false,"given":"Andr\u00e9s","family":"Calvillo-T\u00e9llez","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n y Desarrollo de Tecnolog\u00eda Digital, Instituto Polit\u00e9cnico Nacional, Tijuana 22414, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7994-9774","authenticated-orcid":false,"given":"Everardo","family":"Inzunza-Gonzalez","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda Arquitectura y Dise\u00f1o, Universidad Aut\u00f3noma de Baja California, Ensenada 22860, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,21]]},"reference":[{"key":"ref_1","unstructured":"CONADIS (2023). Guidelines for the Teaching of Mexican Sign Language, Secretariat of Welfare."},{"key":"ref_2","unstructured":"INEGI (2023). Censo Nacional de Poblaci\u00f3n y Vivienda 2023, Instituto Nacional de Estad\u00edstica y Geograf\u00eda. Available online: https:\/\/www.inegi.org.mx\/app\/tabulados\/interactivos\/?pxq=Discapacidad_Discapacidad_02_2c111b6a-6152-40ce-bd39-6fab2c4908e3&idrt=151&opc=t."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Piaget, J. (1952). The Origins of Intelligence in Children, International Universities Press.","DOI":"10.1037\/11494-000"},{"key":"ref_4","unstructured":"Vygotsky, L.S. (1978). Mind in Society: The Development of Higher Psychological Processes, Harvard University Press."},{"key":"ref_5","unstructured":"UNESCO (2022). ICT Accessibility Policy Guidelines: Inclusive Education for All, UNESCO Publishing."},{"key":"ref_6","unstructured":"Lantolf, J.P. (2011). Sociocultural Theory and the Genesis of Second Language Development, Oxford University Press."},{"key":"ref_7","unstructured":"Gonz\u00e1lez-Torres, J., Mart\u00ednez, A., and L\u00f3pez, M. (2020). Lineamientos Biling\u00fces Espa\u00f1ol\u2013LSM Para Educaci\u00f3n Inclusiva, Secretar\u00eda de Educaci\u00f3n P\u00fablica (SEP)."},{"key":"ref_8","unstructured":"UNESCO (2024). Global Education Monitoring Report 2024: Technology and Inclusion in Latin America, UNESCO Publishing."},{"key":"ref_9","unstructured":"Dalal, N., and Triggs, B. (2005, January 20\u201325). Histograms of oriented gradients for human detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), San Diego, CA, USA."},{"key":"ref_10","unstructured":"Howard, A., Sandler, M., Chu, G., Chen, L.-C., Chen, B., Tan, M., Wang, W., Zhu, Y., Pang, R., and Vasudevan, V. (November, January 27). Searching for MobileNetV3. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Republic of Korea."},{"key":"ref_11","unstructured":"Tan, M., and Le, Q.V. (2019, January 9\u201315). EfficientNet: Rethinking model scaling for convolutional neural networks. Proceedings of the 36th International Conference on Machine Learning (ICML 2019), Long Beach, CA, USA."},{"key":"ref_12","first-page":"107369","article-title":"Evaluating adaptive mobile learning systems: Metrics and models","volume":"136","author":"Tzafilkou","year":"2022","journal-title":"Comput. Hum. Behav."},{"key":"ref_13","unstructured":"NASA (Talking Glove Prototype for Gesture-Based Communication, 1977). Talking Glove Prototype for Gesture-Based Communication, NASA Technical Report."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/38.250916","article-title":"A survey of glove-based input","volume":"14","author":"Sturman","year":"1994","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Pigou, L., Dieleman, S., Kindermans, P.J., and Schrauwen, B. (2014). Sign language recognition using convolutional neural networks. Computer Vision (ECCV Workshops), Springer.","DOI":"10.1007\/978-3-319-16178-5_40"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yan, S., Xiong, Y., and Lin, D. (2018, January 2\u20137). Spatial temporal graph convolutional networks for skeleton-based action recognition. Proceedings of the AAAI Conference on Artificial Intelligence, New Orleans, LA, USA.","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"ref_17","unstructured":"SignAll Technologies (2022). SignAll ASL Translation System: Technical Overview, SignAll."},{"key":"ref_18","unstructured":"Koller, O., Zargaran, S., Ney, H., and Bowden, R. (2016, January 27\u201330). DeepASL: Continuous sign language recognition using CNN\u2013LSTM architectures. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ma, N., Zhang, X., Zheng, H.-T., and Sun, J. (2018, January 8\u201314). ShuffleNet V2: Practical guidelines for efficient CNN architecture design. Proceedings of the European Conference on Computer Vision (ECCV 2018), Munich, Germany.","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.1109\/TPAMI.2015.2461544","article-title":"ModDrop: Adaptive multi-modal gesture recognition","volume":"38","author":"Neverova","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_21","first-page":"1235","article-title":"Sign language recognition from video: A review","volume":"45","author":"Cao","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/TMMS.1970.299942","article-title":"AI in CAI: An Artificial Intelligence Approach to Computer-Assisted Instruction","volume":"11","author":"Carbonell","year":"1970","journal-title":"IEEE Trans. Man Mach. Syst."},{"key":"ref_23","first-page":"35","article-title":"Guidon: A tutorial system for teaching medical diagnosis","volume":"1","author":"Clancey","year":"1983","journal-title":"Artif. Intell. Med."},{"key":"ref_24","first-page":"104713","article-title":"Reinforcement-based adaptive feedback improves retention in deaf learners: An empirical study","volume":"195","author":"Martin","year":"2023","journal-title":"Comput. Educ."},{"key":"ref_25","first-page":"1125","article-title":"Dynamic visual-emphasis adaptation reduces gesture-error rates in sign-language learning systems","volume":"24","author":"Zhao","year":"2024","journal-title":"Sensors"},{"key":"ref_26","first-page":"1221","article-title":"Multimodal emotion recognition for adaptive learning environments: A deep neural approach","volume":"14","author":"Zhao","year":"2023","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_27","unstructured":"Feichtenhofer, C., Fan, H., Xiong, B., and Girshick, R. (2022, January 19\u201324). Masked autoencoders for video: Learning temporal structure without labels. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA."},{"key":"ref_28","unstructured":"McMahan, H.B., Moore, E., Ramage, D., Hampson, S., and Aguera y Arcas, B. (2017, January 20\u201322). Communication-efficient learning of deep networks from decentralized data. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), Fort Lauderdale, FL, USA."},{"key":"ref_29","unstructured":"Liu, J., Wang, X., Huang, Z., Chen, Y., and Xu, C. (2024, January 6\u201312). SignBERT: Pretrained sign-language representation learning with multilingual gesture embeddings. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV 2024), Milan, Italy."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Immanuel, J., and Berrezueta-Guzman, S. (2025). Accessible American Sign Language Learning in Virtual Reality via Inverse Kinematics. Virtual Worlds, 4.","DOI":"10.3390\/virtualworlds4040057"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Alsharif, B., Alalwany, E., Ibrahim, A., Mahgoub, I., and Ilyas, M. (2025). Real-Time American Sign Language Interpretation Using Deep Learning and Keypoint Tracking. Sensors, 25.","DOI":"10.3390\/s25072138"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"153","DOI":"10.3102\/0034654307313795","article-title":"Focus on formative feedback","volume":"78","author":"Shute","year":"2008","journal-title":"Rev. Educ. Res."},{"key":"ref_33","unstructured":"Toro-Ossaba, A., Jaramillo-Tigreros, J., Tejada, J.C., Pe\u00f1a, A., L\u00f3pez-Gonz\u00e1lez, A., and Castanho, R.A. (2023). EMG Hand Gesture Dataset, Zenodo."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1080\/10447310802205776","article-title":"An empirical evaluation of the System Usability Scale","volume":"24","author":"Bangor","year":"2008","journal-title":"Int. J. Hum.\u2013Comput. Interact."},{"key":"ref_35","unstructured":"Li, Y., Zhang, H., and Chen, W. (2024). Dynamic Sampling Rate Adjustment for Mobile Sign Language Recognition. Appl. Sci., 14."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/1\/61\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T05:18:11Z","timestamp":1769145491000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/1\/61"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,21]]},"references-count":35,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["fi18010061"],"URL":"https:\/\/doi.org\/10.3390\/fi18010061","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,21]]}}}