Andragogic heterogeneity in cognitive competences for research
Keywords:
heterogeneity, andragogic learning, cognitive skills, researcher, higher educationAbstract
In the current context, the importance of having human capital capable of responding in a concrete and effective way to events that require a research profile has become evident, being essential to have the ability to materialize intellectual virtues in favor of general well-being. However, this is a difficult objective to carry out, provided that there is a lack of scientific training aimed at encouraging future professionals to be high-level researchers, explained by the significant differences between the transversal competences that they should have, in this case, in university higher education. Mainly, the cognitive instrumental competences, manifest the basic and essential characteristics, highly linked to the development of the scientific method. In this sense, the present work shows the diagnosis started in march 2019 and concluded in april 2020, regarding the existing heterogeneity in the cognitive competences for research that the participants should have (ideally), regarding what they manifest when they are in the process of preparing a thesis (actual status); as part of the research courses in the business sciences career and within the framework of the andragogic learning process.
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Aiquipa, J., Ramos, C., Curay, R., & Guizado, L. (2018). Determining factors in carrying out or not a thesis in psychology students. Purposes and Representations, 6 (1), 21-82.
Alonso, P. (2012). Andragogy as a knowledge-promoting discipline in higher education. Educare electronic magazine, 16 (1), 42-58.
World Bank. (2017). Decisive moment. Higher education in Latin America and the Caribbean. Washintong DC .: World Bank. Retrieved from https://openknowledge.worldbank.org/bitstream/handle/10986/26489/211014ovSP.pdf?sequence=5&isAllowed=y
Benarroch, A., & Núñez, I. (2015). Learning of scientific competences versus learning of specific contents. An evaluation proposal. Science Teaching, 33 (2), 9-27. https://doi.org/10.5565/rev/ensciencias.1578
Borja, M. (May 15, 2019). University dropout 42% in Latin America. Obtained from El Búho Magazine: https://elbuho.pe/2019/05/desercion-universitaria-alcanza-el-30-en-peru-y-42-en-latinoamerica/
Castillo, F. (2018). Andragogy, andragogues and their contributions. Of education, 6 (3), 64-76.
Dávila, D. (February 1, 2017). Why is so little research done in Peruvian universities? Obtained from Ciencias.pe: https://www.ciencias.pe/opini%C3%B3n/%C2%BFpor-qu%C3%A9-se-investiga-tan-poco-en-las-universidades-peruanas
García, F., Fonseca, G., & Concha, L. (2015). Learning and academic performance in higher education. Research News in Education, 15 (3), 1-26. Retrieved from https://www.redalyc.org/pdf/447/44741347019.pdf
García, J. (2011). Competency-based educational model: importance and need. Research News in Education, 11 (3), 1-24. Retrieved from https://www.redalyc.org/articulo.oa?id=44722178014
García, J. (2019). Fear of doing a university thesis? A series of recommendations to avoid torture in its preparation. Marine Sciences, 23 (67), 53-65. Retrieved from https://www.researchgate.net/publication/334507325_Fear_to_realize_a_thesis_university_thesis_A_serie_of_recomendaciones_para_avitar_la_tortura_en_your_elaboracion
Healey, M., & Jenkins, A. (2009). Undergraduate Research and Inquiry. New York: Higher Education Academy.
National Institute of Statistics and Informatics. (2015). National University Census. Lima: National Institute of Statistics and Informatics. Retrieved from https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1298/Libro.pdf
Peralta, J. (March 30, 2019). More research is urgently needed in universities. Obtained from Official Gazette El Peruno: https://elperuano.pe/noticia-urge-mayor-investigacion-las-universidades-77107.aspx
Sanz, L. (2010). Cognitive competence in Higher Education. Madrid: Narcea SA editions.
Poongodi, M., Nguyen, T. N., Hamdi, M., & Cengiz, K. (2021). A Measurement Approach Using Smart-IoT Based Architecture for Detecting the COVID-19. Neural Processing Letters, 1-15.
Poongodi, M., Malviya, M., Hamdi, M., Vijayakumar, V., Mohammed, M. A., Rauf, H. T., & Al-Dhlan, K. A. (2021). 5G based Blockchain network for authentic and ethical keyword search engine. IET Commun, 1-7.
Poongodi, M., Malviya, M., Kumar, C., Hamdi, M., Vijayakumar, V., Nebhen, J., & Alyamani, H. (2021). New York City taxi trip duration prediction using MLP and XGBoost. International Journal of System Assurance Engineering and Management, 1-12.
Rawal, B. S., Manogaran, G., Singh, R., Poongodi, M., & Hamdi, M. (2021, June). Network Augmentation by Dynamically Splitting the Switching Function in SDN. In 2021 IEEE International Conference on Communications Workshops (ICC Workshops) (pp. 1-6). IEEE.
Poongodi, M., Malviya, M., Hamdi, M., Rauf, H. T., Kadry, S., & Thinnukool, O. (2021). The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic. Ieee Access, 9, 97906-97928.
M. M. Kamruzzaman, ""New Opportunities, Challenges, and Applications of Edge-AI for Connected Healthcare in Smart Cities,"" 2021 IEEE Globecom Workshops (GC Wkshps), 2021, pp. 1-6, doi: 10.1109/GCWkshps52748.2021.9682055."
Md Selim Hossain, MM Kamruzzaman, Shuvo Sen, Mir Mohammad Azad, Mohammad Sarwar Hossain Mollah, Hexahedron core with sensor based photonic crystal fiber: An approach of design and performance analysis," Sensing and Bio-Sensing Research, 32, 100426
Mingju Chen, Xiaofeng Han, Hua Zhang, Guojun Lin, M.M. Kamruzzaman, Quality-guided key frames selection from video stream based on object detection, Journal of Visual Communication and Image Representation, Volume 65, 2019, 102678, ISSN 1047-3203
M. M. Kamruzzaman: Performance of Decode and Forward MIMO Relaying using STBC for Wireless Uplink. JNW 9(12): 3200-3206 (2014)
M. M. Kamruzzaman, "Performance of Turbo Coded Vertical Bell Laboratories Layered Space Time Multiple Input Multiple Output system," Computer and Information Technology (ICCIT), 2013 16th International Conference on, Khulna, 2014, pp. 455-459.
Yan Zhang, M. M. Kamruzzaman, and Lu Feng “Complex System of Vertical Baduanjin Lifting Motion Sensing Recognition under the Background of Big Data,” Complexity, vol. 2021, Article ID 6690606, 10 pages, 2021. https://doi.org/10.1155/2021/6690606
Md Hossain, MM Kamruzzaman, Shuvo Sen, Mir Mohammad Azad, Mohammad Sarwar Hossain Mollah, Hexahedron Core with Sensor Based Photonic Crystal Fiber,2021
Md Nazirul Islam Sarker, Md Lamiur Raihan, Yang Peng, Tahmina Chumky, MM Kamruzzaman, Roger C Shouse, Huh Chang Deog, "COVID-19: Access to Information, Health Service, Daily Life Facility and Risk Perception of Foreigners during Coronavirus pandemic in South Korea," Archives of Medical Science, 2021, https://doi.org/10.5114/aoms/141164
Y. Shi, S. Wang, S. Zhou and M. M. Kamruzzaman. (2020). Study on Modeling Method of Forest Tree Image Recognition Based on CCD and Theodolite. IEEE Access, vol. 8, pp. 159067-159076, 2020, doi: 10.1109/ACCESS.2020.3018180
Guobin Chen, Zhiyong Jiang, M.M. Kamruzzaman. (2020). Radar remote sensing image retrieval algorithm based on improved Sobel operator, Journal of Visual Communication and Image Representation, Volume 71, 2020, 102720, ISSN 1047-3203 https://doi.org/10.1016/j.jvcir.2019.102720.
Yuanjin Xu, Ming Wei, M.M. Kamruzzaman, Inter/intra-category discriminative features for aerial image classification: A quality-aware selection model,Future Generation Computer Systems,Volume 119,2021,Pages 77-83,ISSN 0167-739X,https://doi.org/10.1016/j.future.2020.11.015.
Xing Li, Junpei Zhong, M.M. Kamruzzaman, “Complicated robot activity recognition by quality-aware deep reinforcement learning”, Future Generation Computer Systems,Volume 117, 2021, Pages 480-485.
Bin Yuan, M. M. Kamruzzaman, Shaonan Shan, "Application of Motion Sensor Based on Neural Network in Basketball Technology and Physical Fitness Evaluation System", Wireless Communications and Mobile Computing, vol. 2021, Article ID 5562954, 11 pages, 2021. https://doi.org/10.1155/2021/5562954
Chi, Z., Jiang, Z., Kamruzzaman, M.M. et al. Adaptive momentum-based optimization to train deep neural network for simulating the static stability of the composite structure. Engineering with Computers (2021). https://doi.org/10.1007/s00366-021-01335-5
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