About
16
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Introduction
Alaa Aldahdouh is a PhD holder from University of Minho, in Education Technology. He has a computer engineering degree with more than 10 years of experience in software development. His major area of interest resides in investigating AI in education, online learning, digital literacy, online experience, learning theories, connectivism, MOOC, and higher education.
Current institution
Additional affiliations
June 2006 - December 2013
Education
July 2014 - May 2018
Publications
Publications (16)
Over the last years, educators have been forced to rethink about the whole education system. In 2005, Connectivism, a new learning theory, was emerged. Consequently, Massive Open Online Courses (MOOCs) have been presented as an alternative powerful educational system. Money was invested and tens of for-profit and non-profit companies involved in pr...
Connectivism was presented as a learning theory for the digital age and connectivists claim that recent developments in Artificial Intelligence (AI) and, more specifically, Artificial Neural Network (ANN) support their assumptions of knowledge connectivity. Yet, very little has been done to investigate this brave allegation. Does the advancement in...
Emotion has long been a question of great interest in a wide range of fields. As a general rule, emotions are categorized as positive, which we seek, and negative, from which we turn away. However, empirically-backed connectivists claim that even negative emotions produce positive effects on student performance. What is less clear is how this proce...
Although extensive research has been carried out on massive open online courses (MOOCs) as representative of connectivist environment, none of them has succeeded to enlighten our understanding about the individual learning experience in connectivist environment at higher educational context. This paper taped into this crucial issue and traced the i...
A considerable amount of literature has recently appeared around the theme of learning networks and Connectivism. However, our understanding of how and why students navigate learning networks in the way they do is limited and the field lacks empirical studies investigating how students form connections. This paper presents a model showing how stude...
Purpose
This paper aims to examine the devastating effects of the ongoing conflict in Gaza on its education system, a phenomenon termed “Educide”. The study documents the systematic destruction of educational infrastructure, including schools and universities, as well as the targeted killing of students and educators, which impedes current and futu...
What we know about the development of online teaching expertise during the COVID-19 pandemic is scarce. Current research has concentrated primarily on the obstacles encountered by university teachers, leaving a significant gap in our understanding of the strategies they employ not only to survive but to flourish in online teaching. Furthermore, the...
This chapter will discuss issues related to analysing empirical data in the research field of professional learning and development using Bayesian statistics. It will start by briefly explaining why the frequentist (so-called classical) approach to analysing empirical data in professional learning and development research is so popular. Also, some...
This is a presentation for the PhD thesis entitled:
Can Connectivism Explain How Students learn?
For Dr. Alaa AlDahdouh, under the supervision of Prof. Antonio Osorio and Prof. Susana Caires
This paper explores the ways in which higher education students search for information in fragile and conflict-affected contexts. Data for this study was drawn from verbal reports of nine participants engaged in retrospective think-aloud sessions to solve ten tasks each. The results of the thematic analysis revealed that the participants followed t...
This poster describes the findings of a published paper entitled:
Jumping from one resource to another: how do students navigate learning networks?
Sequence analysis has been widely used to investigate the patterns of similarities and differences of sequential data in biology and sociology. However, the debate on the usage of sequence analysis in social sciences has not been settled yet. Among a long list, sequence analysis methods have been criticized for ignoring the qualitative information...
Behaviorism, Cognitivism, Constructivism and other growing theories such as Actor-Network and Connectivism are circulating in the educational field. For each, there are allies who stand behind research evidence and consistency of observation. Meantime, those existing theories dominate the field until the background is changed or new concrete eviden...
A Proposed Model of using Facebook at Palestinian Universities
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This study aims to design a model for using Facebook social network at Palestinian Universities. In order to achieve this goal, the researcher studied the current usage of the network at the Palesti...
Questions
Questions (8)
Most of recent books in longitudinal data analysis I have come through have mentioned the issue of unbalanced data but actually did not present a solution for it. Take for example:
- Hoffman, L. (2015). Longitudinal analysis: modeling within-person fluctuation and change (1 Edition). New York, NY: Routledge.
- Liu, X. (2015). Methods and applications of longitudinal data analysis. Elsevier.
Unbalanced measurements in longitudinal data occurs when participants of a study are not measured at the exact same points of time. We gathered big, complex and unbalanced data. Data comes from arousal level which is measured every minute (automatically) for a group of students while engaging in learning activities. Students were asked to report on what they felt while in the activities. Considering that not all students were participating in similar activities in the same time and not all of them were active in reporting their feelings, we end up with unstructured and uncontrolled data which does not reflect a systematic and regular longitudinal data. Add to this issue the complexity of the arousal level itself. Most of longitudinal data analysis assume the linearity (the outcome variable changes positively/negatively with the predictors). Clearly that does not apply to our case, since the arousal level fluctuates over time.
My questions:
Can you please specify a useful resource (e.g., book, article, forum of experts) to analysis unbalanced panel data?
Do you have yourself any idea on how one can handle unbalanced data analysis?
