Promising Emerging Technologies for Teaching and Learning: Recent Developments and Future Challenges

Almufarreh, Ahmad; Arshad, Muhammad

doi:10.3390/su15086917

Cited by 31 publications

(16 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The current study utilized SmartPLS 4.0 to derive Cronbach’s alpha and composite reliability values to indicate internal consistency between items and constructs. The study showed that the values of Cronbach’s alpha coefficient and composite reliability were greater than 0.7, indicating that the data collection instrument was internally consistent with the items ( Hair et al, 2020 ; Almufarreh and Arshad, 2023 ), and as shown in Table 5 , the values of Cronbach’s alpha coefficient and composite reliability both passed, proving that the items for each variable were internally consistent and reliable. Second, this study measured construct validity by extracting the average variance, and the literature suggests that the AVE values are at least 0.5 or higher, assuming that each variable meets the criterion for construct validity ( Hair et al, 2020 ; Almufarreh and Arshad, 2023 ), as shown in Table 5 , the AVE values are all greater than 0.5, indicating good construct validity.…”

Section: Research Design and Methodologymentioning

confidence: 87%

What keeps historical theme park visitors coming? Research based on expectation confirmation theory

Yuan,

Marzuki

2024

Front. Psychol.

View full text Add to dashboard Cite

Culture is one of the most important factors in attracting tourists and influencing the tourist experience. In China, “theme park” is a new field of tourism research, an excellent theme park can not only drive the development of a city’s tourism industry, but also help it better publicize its history and culture. The article takes Kaifeng, China as the background, and selects the Song Dynasty historical and cultural theme park, which was established based on the traditional ink painting Qingming Riverside Drawing, as an example, to study the factors affecting tourists’ travel experience in historical and cultural theme parks, and based on which it explores the reasons for the formation of tourists’ satisfaction and post-trip behavioral intentions, to provide references and suggestions for the development of cultural theme parks from the point of view of travel experience. Based on the expectation confirmation theory, this essay introduces five constructs, namely, expectation (tourism motivation), performance (service quality), confirmation (tourism experience), satisfaction, and post-trip behavior intention, to construct a model of the factors influencing tourists’ satisfaction by tourism experience in historical theme parks and analyze the intrinsic correlation among the factors within the model. It is found that tourists’ tourism experience is mainly affected by tourism motivation and service quality, satisfaction and post-trip behavior intention are jointly determined by the above three. According to the research results, this study believes that tourism motivation, service quality, and tourism experience should be the focus of attention of the current tourist destinations, therefore, focusing on tourists’ motivation to optimize the quality of service, helping tourists to enhance the sense of tourism experience, and improving based on the above focuses is of great significance to promote the development of historical and cultural theme parks.

show abstract

Section: Research Design and Methodologymentioning

confidence: 87%

What keeps historical theme park visitors coming? Research based on expectation confirmation theory

Yuan,

Marzuki

2024

Front. Psychol.

View full text Add to dashboard Cite

show abstract

“…The importance of English courses is increasing, and relevant professionals have investigated in-depth college students learn English on their terms and suggested appropriate personalized English learning strategies employing IoT and big data analysis. In this paper [13], the authors provided an in-depth architecture for an IoT-enabled platform for studying college English that enables personalized learning experiences using data analytics. Depending on student data analysis, machine learning algorithms can quickly customize instructional materials and feedback.…”

Section: Related Workmentioning

confidence: 99%

IoT-enabled Personalized English Learning in Colleges using Big Data Analysis and Decision Support System

2023

Preprint

View full text Add to dashboard Cite

In recent years, the achievements of technology, particularly in the Internet of Things (IoT) and computer technology, have hastened their incorporation into education. To create novel educational opportunities for improving the effects of teaching and learning on management decision-making. On the other hand, this study represents establishing a personalized, IoT-enabled environment for learning college English that employs big data analysis and a decision support system based on a data mining algorithm. Educational analytics generates useful learning outcomes by analyzing provided data, enhancing numerous personalized learning experiences in Chinese, French, and English. The study aims to improve college and university students' English learning experiences using IoT devices, classroom data collection, and data mining techniques. Big data analysis examines the collected data, yielding insightful results that improve real-time customization of English learning experiences. The recommended platform includes an intelligent decision-support system that uses the ARTXP algorithm data mining model based on time series data from English learning resources downloaded by college students to provide each user with personalized educational instructions. The building structure includes a specific information model based on student profiles and preferred learning methods. The site's database of learning resources is available in English knowledge points. The expectation-maximization (E.M.) strategy groups users with similar learning patterns, whereas the recommendation model selects and predicts learning outcomes for adjacent users. The approach employs time series data from English language learning resources and is built on the Cross-Industry Standard Process for Data Mining (CRISP-DM) paradigm. The platform's accuracy, precision, and stability are demonstrated in testing results, emphasizing its ability to significantly boost the efficacy of college English learning.

show abstract

“…All forms of learning process can be carried out easily because of technological assistance. According to (Almufarreh & Arshad, 2023) technological advancements have significantly influenced the education landscape, propelling traditional teaching methodologies into immersive and interactive learning experiences. Researchers continued comparing newly developed technologies to traditional media hoping for an educational revo-lution because now this technology will change learning fundamentally (Bozkurt, 2020).…”

Section: Introductionmentioning

confidence: 99%

The Implementation of Augmented Reality-Based Learning Media on Civics Subject to Increase Learning Motivation of Elementary School Students

Firgiyana,

Arief Cahyo Utomo

2024

jcp

View full text Add to dashboard Cite

This research is motivated by the low motivation of students to learn because the learning process tends to use traditional methods. The development of science and technology that is increasingly sophisticated can be utilized by teachers in using learning media. However, in reality, many teachers do not utilize the use of technology in teaching and learning activities. One of the media that can be used in the learning process is Augmented Reality-based media. The purpose of this study is to determine the implementation of Augmented Reality-based learning media to increase the learning motivation of VI grade students at SDN 01 Kenokorejo. This research employed a quantitative study with a quasi-experimental design using Single-Group Interupted Time-Series Design. This type of design only uses one class, namely the test class. The sample involved 14 students consisting of: 10 male students and 4 female students. The instrument used was a learning motivation questionnaire. Data collection techniques were through observation and questionnaires,. Prerequisite tests, namely normality test and homogeneity test and homegity test (T-test) through SPSS was used as the data analysis technique. The results of the univariate normality test were 0.16, which means > from 0.05, the data was declared "Normal". The univariate homogeneity test was 0.804, which means > from 0.05, it was declared "Homogeneous Data" and the homogeneity test (T-test) was 0.000 <0.05. This shows that there is a significant influence on the difference in the results of the learning motivation questionnaire. Based on the results of the study, it can be concluded that student learning motivation has increased. This is evident from the average score obtained by students from 68,14 to 83,92; so that the implementation of this learning media is effective in increasing student learning motivation.

show abstract

Promising Emerging Technologies for Teaching and Learning: Recent Developments and Future Challenges

Cited by 31 publications

References 80 publications

What keeps historical theme park visitors coming? Research based on expectation confirmation theory

What keeps historical theme park visitors coming? Research based on expectation confirmation theory

IoT-enabled Personalized English Learning in Colleges using Big Data Analysis and Decision Support System

The Implementation of Augmented Reality-Based Learning Media on Civics Subject to Increase Learning Motivation of Elementary School Students

Contact Info

Product

Resources

About