This dataset describes two main variables, technological pedagogical and content knowledge (TPACK) and Beliefs on ICT, which may affect pre-service teachers' (PSTs) use of ICT (UICT) during teaching practices. TPACK assumes that PSTs should actively combine some domains of knowledge to design good quality of ICT-integrated courses lessons. Beliefs on ICT in this study consist of a mix of behavioral, normative, and control beliefs on ICT integration in education. In addition, UICT is defined as ICT used by PSTs during teaching practices. Three approaches were applied for the purification of the dataset; development of instruments, survey, and exploratory factor analysis (EFA). The dataset consists of demographic information, TPACK, Beliefs on ICT, and UICT. The dataset is beneficial to teacher educators in designing effective programs that best nurture PSTs' UICT during teaching practices. Researchers sharing similar sample characteristics in developing countries may adapt this dataset for more rigorous statistical analyses.
Researchers in educational psychology have researched Teacher Self-Concept (TSC) and Teacher Efficacy (TE) as two main predictors predicting burnout. Guided by a model developed by Zhu, Liu, Fu, Yang, Zhang & Shi (2018), the researchers aimed at building a model involving TSC, TE, and three components of burnout; Emotional Exhaustion (EE), Depersonalization (DP), and Reduced Personal Accomplishment (RPA) through Structural Equation Modeling (SEM). The researchers investigated predicting factors of burnout by reporting TSC and TE that might directly affect the components and examine the probability of TE to become a mediator of the correlation between TSC and burnout. This research also examined whether the difference emerges constantly among demographic information (gender and teaching experience) regarding all involved variables. A sample of 876 teachers across three Indonesian provinces completed a printed form of questionnaires. Some statistical procedures namely Content Validity Index (CVI), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Covariance-Based Structural Equation Modeling (CB-SEM), and t-test were conducted. Findings informed that the model is valid and reliable. TSC could directly affect EE, DE, and RPA, as well as indirectly influence them mediated by TE. Besides, TE is also reported to have significant relationships with EE, DE, and RPA. No significant differences in terms of age and teaching experiences emerge, except for EE.
The dataset presents the relationship between Teacher Self-Concept (TSC) and Teacher Efficacy (TE) as the predictors predicting burnout. Three components of burnout involved are Emotional Exhaustion (EE), Depersonalization (DP), and Reduced Personal Accomplishment (RPA). Various statistical approaches such as Content Validity Index (CVI), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Covariance-Based Structural Equation Modeling (CB-SEM) were addressed. Eight hundred seventy six Indonesian teachers form 3 provinces were willing to get involved by filling in the instrument. The data can be used for the educational institutions and centers to issue policies overcoming burnout among teachers, teachers to understand factors affecting their burnout, and future researchers extend the model offered by this dataset. This dataset is co-submitted from Heliyon entitled "Teachers' burnout: A SEM analysis in an Asian context" [1].
This dataset presents the validation process of a survey of factors affecting Indonesian K-12 school teachers' Teachers' Information and Communication Technology Access (TICTA). An initial instrument was developed through the adaptation of instruments from previous studies. Afterward, it was piloted to 120 teachers and tested for its reliability. For the main data collection, the instrument was distributed online and responded by 2775 Indonesian K-12 school teachers. The main data analysis was conducted for the measurement model using four assessments; reflective indicator loadings, internal consistency reliability, convergent, and discriminant validity. The Partial Least Square Structural Equation Model (PLS-SEM) was utilized for the analysis. The dataset is beneficial for educational regulators in providing appropriate access to ICT in K-12 education and for educational researchers for future research on technology access in teaching.
Metaverse, which combines a number of information technologies, is the Internet of the future. A media for immersive learning, metaverse could set future educational trends and lead to significant reform in education. Although the metaverse has the potential to improve the effectiveness of online learning experiences, metaverse-based educational implementations are still in their infancy. Additionally, what factors impact higher education students' adoption of the educational metaverse remains unclear. Consequently, the aim of this study is to explore the main factors that affect higher education students' behavioral intentions to adopt metaverse technology for education. This study has proposed an extended Technology Acceptance Model (TAM) to achieve this aim. The novelty of this study resides in its conceptual model, which incorporates both technological, personal, and inhibiting/enabling factors. The empirical data were collected via online questionnaires from 574 students in both private and public universities in Jordan. Based on the PLS-SEM analysis, the study identifies perceived usefulness, personal innovativeness in IT, and perceived enjoyment as key enablers of students' behavioral intentions to adopt the metaverse. Additionally, perceived cyber risk is found as the main inhibitor of students' metaverse adoption intentions. Surprisingly, the effect of perceived ease of use on metaverse adoption intentions is found to be insignificant. Furthermore, it is found that self-efficacy, personal innovativeness, and perceived cyber risk are the main determinants of perceived usefulness and perceived ease of use. While the findings of this study contribute to the extension of the TAM model, the practical value of these findings is significant since they will help educational authorities understand each factor's role and enable them to plan their future strategies.
The Covid-19 outbreak necessitated the implementation of social distancing mechanisms, such as the enforcement of lockdowns in numerous nations. The lockdown has disrupted many parts of everyday life, but this unusual event has particularly affected education. The temporary closure of educational institutions ushered in dozens of new reforms, including a shift into the distance and online learning. This study investigates the transition from traditional education in physical classrooms to online and distance and online learning in pharmacy education during Covid-19, especially about the challenges and benefits of distance and online learning. We did Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for literature sources between 2020 and 2022 (n.14). The study elaborates on how the transition has influenced teachers and students of pharmacy education. The research also summarizes several recommendations, which may assist in minimizing the adverse impacts of lockdown and encourage streamlined processes to distance and online learning, particularly in pharmacy education.
Conference abstracts: Malaysia in affiliation
(1). PO-211. AGE-SPECIFIC STRESS-MODULATED
CHANGES OF SPLENIC IMMUNOARCHITECTURE
IN THE GROWING BODY. Marina Yurievna Kapitonova, Syed Baharom Syed Ahmad Fuad, Flossie Jayakaran; Faculty of Medicine, Universiti Teknologi MARA, Shah Alam, Malaysia
[email protected] (2). PO-213. A DETAILED OSTEOLOGICAL STUDY OF THE ANOMALOUS GROOVES NEAR THE
MASTOID NOTCH OF THE SKULL. ISrijit Das, 2Normadiah Kassim, lAzian Latiff, IFarihah Suhaimi, INorzana Ghafar, lKhin Pa Pa Hlaing, lIsraa Maatoq, IFaizah Othman; I Department of Anatomy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia; 2 Department of Anatomy, Universiti Malaya, Kuala Lumpur, Malaysia. das_sri [email protected] (3). PO-21S. FIRST LUMBRICAL MUSCLE OF THE
PALM: A DETAILED ANATOMICAL STUDY WITH
CLINICAL IMPLICATIONS. Srijit Das, Azian Latiff, Parihah Suhaimi, Norzana Ghafar, Khin Pa Pa Hlaing, Israa Maatoq, Paizah Othman; Department of Anatomy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia. [email protected] (4). PO-336. IMPROVEMENT IN EXPERIMENTALLY
INDUCED INFRACTED CARDIAC FUNCTION
FOLLOWING TRANSPLANTATION OF HUMAN
UMBILICAL CORD MATRIX-DERIVED
MESENCHYMAL CELLS. lSeyed Noureddin Nematollahi-Mahani, lMastafa Latifpour, 2Masood Deilami, 3Behzad Soroure-Azimzadeh, lSeyed
Hasan Eftekharvaghefi, 4Fatemeh Nabipour, 5Hamid
Najafipour, 6Nouzar Nakhaee, 7Mohammad Yaghoobi, 8Rana Eftekharvaghefi, 9Parvin Salehinejad, IOHasan Azizi; 1 Department of Anatomy, Kerman University of Medical Sciences, Kerman, Iran; 2 Department of Cardiosurgery, Hazrat-e Zahra Hospital, Kerman, Iran; 3 Department of Cardiology, Kerman University of Medical Sciences, Kerman, Iran; 4 Department of Pathology, Kerman University of Medical Sciences, Kerman, Iran; 5 Department of Physiology, Kerman University of Medical Sciences, Kerman, Iran; 6 Department of Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran; 7 Department
of Biotechnology, Research Institute of Environmental Science, International Center for Science, High Technology & Environmental Science, Kerman, Iran; 8 Students Research Center, Kerman University of Medical Sciences, Kerman, Iran; 9 Institute of Bioscience, University Putra Malaysia,
Kuala Lumpur, Malaysia; 10 Department of Stem Cell, Cell Science Research Center, Royan Institute, ACECR, Tehran, Iran. [email protected] (5).