Descubriendo conocimientos para adecuar estilo de enseñanza

En este trabajo se presenta un proyecto de investigación áulica tendiente a mejorar la calidad del proceso enseñanza-aprendizaje en la asignatura Inteligencia Artificial, de la carrera Ingeniería en Computación de la Universidad Católica de Santiago del Estero. Específicamente se propone descubrir los estilos de aprendizaje dominantes en los estudiantes de la carrera, aplicando el Proceso de Descubrimiento de Conocimiento, para luego en función de los conocimientos descubiertos adecuar el diseño curricular de la asignatura. La propuesta curricular resultante se aplicará sobre la cohorte 2008. La contrastación de los resultados obtenidos por estos estudiantes con los mostrados por las cohortes 2005, 2006 y 2007 permitirá validar la propuesta.Eje: Tecnología informática aplicada en educaciónRed de Universidades con Carreras en Informática (RedUNCI

Descubriendo conocimientos para adecuar estilo de enseñanza

En este trabajo se presenta un proyecto de investigación áulica tendiente a mejorar la calidad del proceso enseñanza-aprendizaje en la asignatura Inteligencia Artificial, de la carrera Ingeniería en Computación de la Universidad Católica de Santiago del Estero. Específicamente se propone descubrir los estilos de aprendizaje dominantes en los estudiantes de la carrera, aplicando el Proceso de Descubrimiento de Conocimiento, para luego en función de los conocimientos descubiertos adecuar el diseño curricular de la asignatura. La propuesta curricular resultante se aplicará sobre la cohorte 2008. La contrastación de los resultados obtenidos por estos estudiantes con los mostrados por las cohortes 2005, 2006 y 2007 permitirá validar la propuesta.Eje: Tecnología informática aplicada en educaciónRed de Universidades con Carreras en Informática (RedUNCI

Design guidelines for self-assessment support for adult academic distance learning

Menendez Blanco, M., Van der Veer, G., Benvenuti, L., & Kirschner, P. A. (2011). Design guidelines for self-assessment support for adult academic distance learning. In H-J Shalin (Ed.), Constructing self-discovery learning spaces online: scaffolding and decision making technologies (pp. 169-198). Hershey, PA: IGI Global.This contribution focuses on adult distance learning. Based on experiences at the Open University of the Netherlands we investigate specific problems that our students have with self-assessment and metacognition while studying. Starting from a literature review and complementing this with available student data from our teaching research center, we developed a conceptual framework that was iteratively adjusted and assessed by a questionnaire study and interviews. This allowed us to develop design guidelines for self-assessment support in distance learning environments. These guidelines were reviewed by experts. The input from the experts was used to modify the guidelines and iterate until they were considered complete. Tangible designs (i.e., mock-ups) for each of the self-assessment methods were proposed. These tangible designs were prototyped for later evaluation. Finally, we provide our conclusions and propose recommendations for actual application and systematic design

E-Learning and learning styles:implementing and evaluation of learning sequence method

This research began by accepting that different people learn differently from one another; have different learning styles, strengths and preferences in the ways they take in and process information. The research reported here asks whether, in Higher Education, and using new online technologies, the learning process can be enhanced by matching it to student learning style. To test this hypothesis blocks of eLearning material to support different learning activities was created for, and delivered to, students on the Computer Technology Module of a first year of a degree in Computer Technology. The author employed Honey and Mumford's (1986) classifications, and each student participating in the research was characterised as having one of four learning styles; Activist, Pragmatist, Reflector or Theorist. The material was designed so that the blocks could be delivered in four different sequences, each sequence in which the blocks was presented matched one of the learning styles. All students were tested to establish their learning style so that there was control of whether or not they were allocated to a group where order of delivery matched learning style. At the end of the course a Post-test assessed progress achieved, and student questionnaires evaluated attitudes towards the online course material and other aspects of the course. Three separate experiments were carried out

Accounting for Social Anxiety in the Online IT Security and Digital Forensics Educational Domain

No one could have anticipated the speed at which technology and social media have developed over the past thirty years. This increased use of technology and social media affectst today's students in some ways. We are now in a spiral that is hard to get out of, and the more we implement technology and ways for people to carry out daily tasks from behind a screen, the fewer people might go out and socialise with the world. Losing the requirement to interact with other human beings means losing the training areas for face-to-face interaction, which could mean losing the ability to be a social member of humanity. The lack of training areas for social activities is especially bad for young adults who already struggle with social anxiety. The primary treatment for this condition is cognitive therapy which moves towards handling the situations that provoke anxiety rather than avoiding them. A drastic increase in the number of devices connected to the Internet affects the need for IT security and digital forensics experts. Moving education online means that many young adults will find themselves doing IT security and digital forensics-related topics in an online environment. Many of these students will have psychological challenges of different sorts. This research aims not to solve these issues, as they are far too complicated for one-size-fits-all solutions. Instead, the study seeks to shed light on students' different social anxieties in an online environment and discuss our new online and technology-driven world's psychological effects on young adults. Educators that develop programs or content and learning material, and deliver the content and teaching, must understand some of the mechanisms surrounding these issues and be aware of the challenges that cause many students to struggle. Although this awareness is valuable and necessary in other areas, as well as IT security and digital forensics education in online domains, it is perhaps logical to focus on this first. The increased need for professionals in this area and the common idea that one can do this work remotely seem tempting for people who struggle with face-to-face social interactions. The results from a questionnaire form the basis of interviews with students with recognised social anxiety. Interviews with online students in general also help this research hopefully enlighten educators to make a difference for many online students in IT security and digital forensics domain and many students in general. This researcher published a questionnaire on the school's learning platform based on the Liebowitz Social Anxiety Scale. The responses show that only around twenty-five per cent of the student cohort has a score indicating that Social Anxiety Disorder is not probable. The low percentage means that a potentially significant portion of students has social anxiety-related challenges at some level. This research also shows that not only online students have this problem. The issues are also present among campus-based students, in fact, more present among campus students, which is surprising. The recent outbreak of Covid-19, pushing students into an online environment they might not have wanted in the first place, also has had a considerable impact. Republishing the questionnaire for comparison for IT and non-IT students during the Covid-19 epidemic and examining the results using SPSS shows only minor differences between the cohorts asked before the Covid-19 epidemic and those asked during the Covid-19 epidemic, with no apparent differences between IT students and non-IT students