Research Article
Narinthon Imjai, Somnuk Aujirapongpan, Jaturon Jutidharabongse, Berto Usman
CONT ED TECHNOLOGY, Volume 16, Issue 1, Article No: ep487
ABSTRACT
Notwithstanding the pervasive utilization of digital technology in social and educational realms, an in-depth understanding and exploration of the interrelationships amongst digital connectivity, social skills, and emotional intelligence, particularly within Generation Z demographic–known for their heavy reliance on digital platforms–remains elusive. This study endeavors to address this gap. Applying structural equation modeling, it examined the interrelationships between digital connectivity, social skills, and emotional intelligence, surveying a sample of 518 Generation Z students (comprising 77.61% females, 20.64% males, and 1.74% non-binary) across various academic years and disciplines at a university located in Southern Thailand. PLS-SEM software was employed to evaluate the structural model and substantiate the research hypotheses. Our findings suggest that digital connectivity did not detrimentally impact social skills. However, it negatively influenced emotional intelligence among Generation Z students, observable both at the operational level and in terms of fostering the capacity to regulate one’s own and others’ emotional states. Despite this, social skills proved to significantly enhance emotional intelligence. The same consistent pattern of a positive and significant influence is observed when testing the indirect effect of digital connectivity on emotional intelligence through social skills. Furthermore, it was found that robust and effective digital connectivity could potentially bolster understanding and management of emotions in the digital age, much like well-developed social skills. Hence, this study provides substantial insights into the nuanced impacts of digital connectivity on the social and emotional development of Generation Z students.
Keywords: digital connectivity, social skills, emotional intelligence, Generation Z students
Research Article
Scott A. Courtney, Mary E. S. Miller, Michael J. Gisondo
CONT ED TECHNOLOGY, Volume 14, Issue 4, Article No: ep387
ABSTRACT
The coronavirus pandemic impacted all aspects of society, causing countries and local communities to close workplaces, move schools to remote instruction, limit in-person contact, cancel public gatherings, and restrict travel. Attempts to mitigate COVID-19 through remote instruction provided unique opportunities for researchers to examine the resources teachers utilize to drive their practices. We examine the impacts of the pandemic on grades 6-12 mathematics teachers and math interventionists, with particular attention to teachers’ integration of digital resources. Using purposive sampling, we surveyed 50 participants—across urban, suburban, and rural districts—throughout the United States. The descriptive survey focused on six aspects of teachers’ practices with digital resources. Results indicate that challenges encountered and lessons learned included a lack of student engagement and motivation, increased distractions, and varied access to technology. Integration of technology did not positively impact students’ mathematical proficiency across all teachers. Common resources used across planning of lessons, implementation of instruction, and assessment included the Google platform, Desmos, and GeoGebra. Where appropriate, we situate our results within the larger context of recent international research. These findings support teacher practices that constantly attempt to optimize students’ mathematics and social emotional learning, regardless of the environment or situation.
Keywords: digital technology, remote instruction, teachers’ mathematics practices, students’ social emotional learning
Review Article
Sergei P. Zhdanov, Kseniia M. Baranova, Natalia Udina, Artem E. Terpugov, Elena V. Lobanova, Oksana V. Zakharova
CONT ED TECHNOLOGY, Volume 14, Issue 3, Article No: ep369
ABSTRACT
The COVID-19 outbreak has wreaked havoc on educational systems on a scale never seen before in history. The closure of schools and other institutions of learning has impacted 94% of the world’s student population. Even school closures, such as those that occur during the summer, have a significant effect on children’s academic ability. The word “learning loss” refers to any loss of information and abilities, whether specific or generic. By Fall 2020, extended absences from school will have a detrimental effect on student achievement. Learning loss is commonly addressed when schools close for extended periods of time during the summer, natural catastrophes, or epidemics. Even brief school closures might result in significant loss of learning. Due to the global nature of the COVID-19 epidemic, special attention was devoted to learning losses.
During the pandemic, learning loss occurs as a result of kids studying at home due to school closures. School closures do not have to result in an equal loss of learning for all students. The variables that contribute to learning loss include “change in teaching methods”, “opportunities to reach education”, “less time for learning”, and “emotional factors”. Reduced instructional time–provided by teachers in accordance with the national curriculum–is likely to result in loss of learning. Due to the disparate scales used in the studies, it is hard to compare the magnitudes of learning losses. However, based on the data from the studies, it is reasonable to assume that these nations are investigating learning losses and that they exist. As a result, there is convincing evidence that students lose more information during lockdown than they do over the course of a normal school year. The elements causing learning losses differ according to context. With the reopening of schools, it is important to establish the actual magnitude of learning losses and to implement remedial measures in order to avoid the emergence of medium- and long-term educational difficulties.
Keywords: learning losses, change in teaching methods, opportunities to reach education, less time for learning, less control/feedback, emotional factors
Research Article
Suthanit Wetcho, Jaitip Na-Songkhla
CONT ED TECHNOLOGY, Volume 14, Issue 2, Article No: ep359
ABSTRACT
In the era of a workforce driven by automation and artificial intelligence, social and emotional skills are becoming increasingly relevant to online learning environments. Since social-emotional learning may be defined as a vital component of the learning process in professional instructional design practices, online learners not only need to develop the ability to apply their knowledge, attitudes, and skills but also to understand and manage their emotions. In which setting and achieving positive goals through social interaction, sharing feelings, and developing empathy for others can help with the process. This paper outlines the possibility of using emotion recognition, and social sharing of emotion techniques to support the regulation of emotion in pre-service teacher education. This study aimed to investigate pre-service teachers’ emotion recognition tools acquired by emotion tracker and physiological signals based on their perceptions (without a concrete experience and knowledge). Moreover, the predictive ability was examined along with the relationships between emotion recognition, social sharing of emotion, and emotion regulation. Finally, we investigated emotion adjustment techniques that can be adapted into mobile computer-supported collaborative learning (mCSCL). In this study, 183 pre-service teachers from three different teacher-education institutions in Thailand, were voluntarily participated based on convenience sampling. The results of a self-report via online survey revealed that most pre-service teachers own at least one of the mobile technologies e.g., smartphones, tablets, or laptops. However, there is an increasing number of additional gadgets and wearable devices like EarPods and smartwatches. At the current time, it is nearly impossible to use of the IoT and other wearable devices. According to their subjective impressions in which corresponded to emotion recognition in the scientific literature, Heart rate (HR) and Heart rate variability (HRV) have recognized the most possibilities for emotion detection among physiological signals. Regarding regression analysis, the two-predictor models of emotion recognition and the social sharing of emotion were also able to account for 31% of the variance in emotion regulation, p<.001, R2=.31, and 95% CI [.70, .77]. In addition, the mCSCL applications and the importance of these variables in different collaboration levels are also discussed.
Keywords: social emotional learning, emotion recognition, social sharing of emotion, emotion regulation, mCSCL
Research Article
Suthanit Wetcho, Jaitip Na-Songkhla
CONT ED TECHNOLOGY, Volume 13, Issue 4, Article No: ep319
ABSTRACT
Self-regulation is an essential skill in teacher development, especially for pre-service teachers who need to develop their own self-regulated skills while simultaneously promoting self-regulation in learners. This study outlines a teacher development program in which pre-service teachers participated in a self-regulatory process in a Mobile Computer-Supported Collaborative Learning (mCSCL) online learning environment. Our aim is to fill the existing gap in this area by adding more collaborative learning processes. This study aimed to investigate the predictive effects that self-evaluation to define tasks and goals (at forethought phase) has on self-reflection, which is mediated by collaboration. Furthermore, we have drawn the possibility of embedding collaboration into the socio-emotional note-taking process by using the concept of mCSCL throughout the self-regulated learning process. Data was collected from undergraduate students, working as pre-service teachers, and studying at two institutes in Thailand (N=147), with 17 items of self-regulatory inventory obtained from the original self-regulatory inventory together with 5 other collaboration developed by the author. Structural equation modelling (SEM) analysis was used to confirm a partial mediation model via direct and indirect effects. Later the path analysis, the qualitative data is acquired to re-design the socio-emotional collaborative note-taking on mCSCL tools during the self-regulatory learning process, corresponding with the model testing phase according to the previous study by a semi-structure interview with 5 pre-service teachers. The results proved that collaboration was found to be a significant partial mediator of self-evaluation and self-reflection, in accordance with the empirical data. With our findings we were able to design a socio-emotional collaborative note-taking activity in the mCSCL setting. We proposed collaborative note-taking activities which collaboration procedure is highlighted throughout 3 phases: collaboration in pre-performance (recording ideas and planning), collaboration during the performance (sharing and brainstorming, support and seeking helps), and collaboration in post-performance (reflecting and evaluating) in which the activity was taking place between instructors and peers during supervision period.
Keywords: self-regulation, collaborative-notetaking, MCSCL, socio-emotional, teacher development
Research Article
Alaba O. Agbatogun, Peter A. Ajelabi, Lawunmi M. Oyewusi
CONT ED TECHNOLOGY, Volume 1, Issue 4, pp. 335-347
ABSTRACT
This study was designed to investigate the relative and combined contributions of cognition and emotion on Nigerian undergraduate students’ level of computer frustration in online environments. A total of 1972 (Male=987, Female=985) students randomly selected from the two state-owned universities in Ogun State of Nigeria participated in the study. The data for the study were collected through the use of Students’ Cognition Scale (SCS), Students’ Emotion Scale (SES) and Students’ Computer Frustration Scale (SCFS). Data analysis involved the use of mean and standard deviation as descriptive statistics as well as Pearson Product Moment Correlation and regression analysis as inferential statistics. The research findings revealed that students encountered various frustrating experiences during e-registration, when a combination of the predictor variables (cognition and emotion) significantly accounted for 2.5% to the variance of the students’ level of frustration during e-registration. Meanwhile, cognition was found as the potent contributor of students’ frustration during e-registration. The results of this study further indicated that there was a statistically significant difference in the level of computer frustration among students of different universities. Recommendations were made according to the findings of the study.
Keywords: Cognition, Emotion, Computers frustration, Online registration