Technology-based Methods Research Articles

Technology-based interventions for tobacco smoking prevention and treatment: a 20-year bibliometric analysis (2003-2022).

Substance abuse, particularly tobacco smoking, is a significant global public health concern. Efforts have been made to reduce smoking prevalence and promote cessation, but challenges, such as nicotine addiction, marketing tactics by tobacco industry, and cultural acceptability hinder progress. Technology has emerged as a potential tool to address these challenges by providing innovative scalable interventions. The objective of the study was to analyze and map scientific literature on technology-based intervention for tobacco prevention and treatment. A bibliometric methodology was conducted. Scopus database was used to retrieve relevant research articles published between 2003 and 2022. The analysis included publication trends, key contributors, research hotspots, research themes, the most impactful articles, and emerging research topics. A total of 639 articles were found, with a slow and fluctuating growth pattern observed after 2011. The Journal of Medical Internet Research was the most prominent journal in the field. The United States was the leading country in the field, followed up by the United Kingdom, and the Netherlands. Research hotspots included smoking cessation, randomized controlled trials, and technology-based methods such as internet, mHealth, smartphone apps, text messages, and social media. Four primary research themes were identified: development of smartphone applications, efficacy of text messaging interventions, acceptance and effectiveness of smartphone applications, and interventions targeting young adults and students using mobile phone and social media platforms. The top 10 cited articles demonstrated effectiveness of digital interventions in promoting smoking cessation rates and reducing relapse rates. Emerging research topics included the use of virtual reality interventions, interventions for specific populations through personalized tools, and technology-based interventions in non-Western countries. The findings of the current study highlight the potential of technology to address the challenges associated with tobacco smoking. Further future research in this area is warranted to continue advancing the field and developing effective and evidence-based interventions to combat tobacco smoking.

Technology-Based Future Science Education: Axiological Philosophy in the Framework of Bibliometric Analysis

Science education is crucial in developing our understanding of the natural world and enhancing knowledge growth. With rapid advancements in information and communication technology, there is a unique opportunity to transform science education into a more interactive, inclusive, and relevant discipline. However, this evolution prompts philosophical questions, especially concerning axiology—the study of the value and impact of technology on the future of science education. This research explores the axiological aspects of technology integration in science education through a bibliometric analysis, focusing on how technology-based methods can enrich science learning. A comprehensive literature review reveals that technology is crucial in making science education more accessible, motivating students, facilitating the acquisition of new skills, fostering critical thinking, and boosting student engagement. It highlights the value of incorporating technology into educational practices and how it aligns with axiological considerations in science education. The findings emphasize the need for a deeper philosophical understanding of technology's role in science education to ensure its ongoing relevance and effectiveness. Looking forward, the integration of technology in science learning promises to advance our knowledge and suggests a fertile area for future research, emphasizing the exploration of innovative technological tools that can further enhance science education for all students.

LGBTQ+ inequity in crowdfunding cancer costs: The influence of online reach and LGBTQ+ state policy.

Emerging literature suggests that LGBTQ+ cancer survivors are more likely to experience financial burden than non-LGBTQ+ survivors. However, LGBTQ+ cancer survivors experience with cost-coping behaviors such as crowdfunding is understudied. We aimed to assess LGBTQ+ inequity in cancer crowdfunding by combining community-engaged and technology-based methods. Crowdfunding campaigns were web-scraped from GoFundMe and classified as cancer-related and LGBTQ+ or non-LGBTQ+ using term dictionaries. Bivariate analyses and generalized linear models were used to assess differential effects in total goal amount raised by LGBTQ+ status. Stratified models were run by online reach and LGBTQ+ inclusivity of state policy. A total of N = 188,342 active cancer-related crowdfunding campaigns were web-scraped from GoFundMe in November 2022, of which N = 535 were LGBTQ+ and ranged from 2014 to 2022. In multivariable models of recent campaigns (2019-2022), LGBTQ+ campaigns raised $1608 (95% CI: -2139, -1077) less than non-LGBTQ+ campaigns. LGBTQ+ campaigns with low (26-45 donors), moderate (46-87 donors), and high (88-240 donors) online reach raised on average $1152 (95% CI: -$1589, -$716), $1050 (95% CI: -$1737, -$364), and $2655 (95% CI: -$4312, -$998) less than non-LGBTQ+ campaigns respectively. When stratified by LGBTQ+ inclusivity of state level policy states with anti-LGBTQ+ policy/lacking equitable policy raised on average $1910 (95% CI: -2640, -1182) less than non-LGBTQ+ campaigns from the same states. Our findings revealed LGBTQ+ inequity in cancer-related crowdfunding, suggesting that LGBTQ+ cancer survivors may be less able to address financial burden via crowdfunding in comparison to non-LGBTQ+ cancer survivors-potentially widening existing economic inequities.

Pengimplementasian Pendidikan Karakter Mengenai Kepedulian Lingkungan Pada Sekolah Sungai Di Gunung Anyar

Character education is important for every individual, especially in terms of environmental awareness. Good character can be formed through education at school. Caring about the environment is important because it will have many positive impacts on every individual. To make this happen, it can be done by instilling various character values in students from an early age. This study aims to strengthen understanding of the importance of protecting the surrounding environment, especially for students at the River School, Gunung Anyar, Surabaya. This study uses conventional learning methods, question and answer methods and technology-based learning methods. In fact, this school has slowly shaped the students' character regarding caring for the environment. It is known that students are able to understand how to protect the environment.

Skaitmeninių metodų taikymas praeities kelionių tyrimuose

The massive digitisation of written historical sources, optical character recognition (OCR) of texts, and their online availability in recent decades have created new opportunities and challenges for historical research. The digital humanities research model presented in this paper is based on the information organisation paradigm and the application of digital technology-based methods in studying ancient travels. The model has been developed and tested using the materials of the project “Homo Viator: Travel Space and Travellers’ Experiences in Early Modern Lithuania”. The main problem of the research is related to the fact that one of the essential sources of information about ancient travel are egodocuments (letters, diaries, memoirs, etc.) that contain journeys described alongside other important life events of a particular person. However, travel descriptions form only a small part of a text of a given egodocument and are unevenly distributed among different egodocuments. Therefore, given the size of the text of the egodocuments and their collections and the number of egodocuments published in different languages, researching them as sources in only one aspect (travel) requires a significant amount of human and time resources. A similar problematic situation exists with other sources of knowledge on ancient travel: a massive number of documents published in digital form (including OCR), their texts are voluminous, and the text fragments related to travel, country descriptions, ancient travel routes, travel and mobility infrastructure, and travellers’ experiences are relatively small and scattered throughout the source text. The research model described in the paper is divided into two steps: (i) collection of the corpus of OCR source texts; (ii) collection of empirical data using a dictionary-based computer-aided [or assisted] qualitative text analysis method implemented with the MaxQDA software. The collection of the source text corpus is carried out by applying the general principles and methods of online search of scientific publications. The corpus comprises authentic, published sources relevant to the study (letters, diaries, memoirs, etc.) and scholarly publications about them, thus forming two blocks of text - sources and literature. The literature block is used as additional material for a more precise selection and interpretation of the source texts. A key element for applying a dictionary-based computer-aided [or assisted] qualitative text analysis method is a high-quality dictionary that accurately describes the concepts (categories) relevant to the research. Considering the specificity of the sources (the languages used in the sources and their translations), a multilingual dictionary (Lithuanian-Polish-English-Russian-German) was compiled. The structure of the dictionary consists of six concepts (categories) related to ancient travel: (i) journey (general description), (ii) road and its infrastructure (bridges, fords, etc.), (iii) means of transportation, (iv) resting and accommodation places (towns, villages, taverns, post offices, etc.), (v) people encountered on the way (inn-keepers, highwaymen, guides, etc.), and (vi) food of the journey. A set of keywords and phrases describes each concept. In the last stage of the study, the research model was tested. The testing showed that the model could solve the above problems that arose during the project.

DC Resistivity and Electromagnetic Induction Techniques for Soil Characterization in the Agriculture Land (Case Study in Cidadap, West Bandung, West Java)

ABSTRACTS Precision farming or precision agriculture is generally defined as information- and technology-based methods used for agricultural optimization. This concept can be applied to increase crop production and minimize the effect of the massive fertilizer use on the environment. The implementation of precision farming develops specific rules based on soil and hydrogeological properties that allow farmers to obtain more information for their crop management. This study used direct Current (DC) geoelectrical and electromagnetic (EM) methods to get the land’s water distribution data by measuring the soil’s resistivity and conductivity. Both methods are best used on preliminary surveys of precision farming because this method could measure the resistivity and conductivity of subsurface properties in the field and green environmental techniques. Measurements were made on agricultural land located in Parompong, Lembang, West Java. ARES II was used to measure the resistivity value, while EM38-MK2 was used to measure the conductivity value. From the processing results and its correlation with the pit test, the resistivity values were obtained in the 15-170 Ω.m range, while the conductivity values were 2-115 mS/m. There are good correlations between geophysical data and test pit data, which correspond to the resistive layers at a depth of 0.75 m and the conductive part at a depth of 1.5 m. DC Geoelectrical and EM methods are used to see the fertility distribution on agricultural land.

Validity of instrument to measure primary school mathematics teachers’ acceptance of m-learning applications

<span lang="EN-US">Mobile learning (M-learning) is one of the proposed technology-based methods for teaching mathematics in today’s education 4.0 era. This method enables teachers to conduct instruction and learning without being bounded by walls, wires, and the need for specialized physical infrastructure and facilities. This study was conducted to develop and validate an instrument for evaluating primary school mathematics teachers’ acceptance of M-learning applications in problem-solving teaching involving six variables. This research is quantitative and utilizes a questionnaire to collect data. This study involved a total of four experts and 120 participants. Cronbach’s alpha and Exploratory Factor Analysis were used to perform a descriptive analysis of the data. Cronbach’s alpha was determined to be 0.934, with a factor eigenvalue greater than 1. The Kaiser–Meyer–Olkin value for each construct is 0.50, whereas Bartlett’s test value is statistically significant (<0.5). Each item has a factor loading of 0.50 and a variance of ≥60%. The findings showed that this instrument contains six constructs and nineteen appropriate items. It also indicated that this instrument could be used to investigate perceptions of the primary school mathematics teachers’ acceptance of m-learning applications in problem-solving teaching instruments involving performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, and usage behavior (attitude).</span>

Innovative solutions for language growth: the impact of problem-based learning via DingTalk on Chinese undergraduates' business vocabulary amid COVID-19.

Amidst the COVID-19, which has necessitated the widespread use of distant learning, there has been a notable increase in the recognition and utilization of inventive pedagogical methods and technological tools in the field of language teaching. The primary objective of this research is to assess the effects of DingTalk-based PBL on the business vocabulary growth of Chinese undergraduates during the pandemic, with a particular focus on remote learning environments. This mixed-methods research employed a sample of 58 participants. The study involved both quantitative vocabulary assessments and qualitative interviews. The quantitative assessments aimed to measure the impact on vocabulary scores, while qualitative interviews were conducted to gather insights into participants' experiences and perceptions regarding DingTalk-based PBL. The quantitative assessment revealed a significant improvement in business vocabulary scores among the participants who underwent DingTalk-based PBL. This result indicates the platform's potential to enhance language acquisition. The qualitative interviews provided further insights, with participants expressing positive attitudes toward DingTalk-based PBL. They emphasized its capacity to sustain engagement, foster collaboration, and bridge the gap between remote learning and effective language acquisition. These findings underscore the transformative potential of DingTalk-based PBL in language education, especially in the context of challenges posed by the pandemic. While recognizing the constraints of this study, such as its limited duration and restricted contextual applicability, the research encourages further investigation into sustainable vocabulary expansion, the development of multifaceted language abilities, and the integration of these platforms into emerging hybrid educational frameworks. This study makes a valuable contribution to the ongoing discourse regarding novel technology-based methods in language instruction, providing relevant insights applicable to both present and future educational contexts.

대학 교양교육의 교수·학습 방법에 대한 연구 동향

Objectives The purpose of this study is to examine trends in research related to teaching and learning methods in university general education. Methods For this study, a total of 107 domestic research papers published between 2012 and July 2023 were selected. Content analysis was employed, and the analysis criteria (including year, teaching and learning methods, academic fields, research objectives, research types, and application environments) were used to conduct fre-quency analysis and cross-analysis. Additionally, word cloud analysis was utilized to analyze the frequency of ap-pearance of keywords in each research paper. Results Firstly, the results of frequency analysis across six domains showed a noticeable recent surge in re-search, particularly in technology-based, discussion-oriented, and problem-based teaching and learning meth-ods, including flipped learning. Humanities emerged as the most frequently studied academic field, with a strong emphasis on effectiveness analysis, application, and case studies. Research types were predominantly mixed or qualitative, and application environments were ranked as offline, blended, and online, in that order. Secondly, cross-domain analysis revealed significant variations in research trends based on research objectives, application environments, and academic fields. Finally, word cloud analysis highlighted keywords such as writing, university, teaching methods, general education, class, English, learner, problem-centered learning, flipped learning, and communication. Conclusions Firstly, it was observed that there is a growing interest and necessity for research in university gen-eral education, particularly in teaching and learning methods. Secondly, with the increasing trend in research based on digital learning environments and technology, it is important for researchers to have a deeper under-standing of these areas. Thirdly, the study indicated the need for extensive follow-up research in academic fields beyond the humanities. Furthermore, it emphasized the importance of balanced and diverse research in terms of research objectives, types, and topics in the context of university general education.

Exploring Online Crowdfunding for Cancer-Related Costs Among LGBTQ+ (Lesbian, Gay, Bisexual, Transgender, Queer, Plus) Cancer Survivors: Integration of Community-Engaged and Technology-Based Methodologies.

Cancer survivors frequently experience cancer-related financial burdens. The extent to which Lesbian, Gay, Bisexual, Transgender, Queer, Plus (LGBTQ+) populations experience cancer-related cost-coping behaviors such as crowdfunding is largely unknown, owing to a lack of sexual orientation and gender identity data collection and social stigma. Web-scraping has previously been used to evaluate inequities in online crowdfunding, but these methods alone do not adequately engage populations facing inequities. We describe the methodological process of integrating technology-based and community-engaged methods to explore the financial burden of cancer among LGBTQ+ individuals via online crowdfunding. To center the LGBTQ+ community, we followed community engagement guidelines by forming a study advisory board (SAB) of LGBTQ+ cancer survivors, caregivers, and professionals who were involved in every step of the research. SAB member engagement was tracked through quarterly SAB meeting attendance and an engagement survey. We then used web-scraping methods to extract a data set of online crowdfunding campaigns. The study team followed an integrated technology-based and community-engaged process to develop and refine term dictionaries for analyses. Term dictionaries were developed and refined in order to identify crowdfunding campaigns that were cancer- and LGBTQ+-related. Advisory board engagement was high according to metrics of meeting attendance, meeting participation, and anonymous board feedback. In collaboration with the SAB, the term dictionaries were iteratively edited and refined. The LGBTQ+ term dictionary was developed by the study team, while the cancer term dictionary was refined from an existing dictionary. The advisory board and analytic team members manually coded against the term dictionary and performed quality checks until high confidence in correct classification was achieved using pairwise agreement. Through each phase of manual coding and quality checks, the advisory board identified more misclassified campaigns than the analytic team alone. When refining the LGBTQ+ term dictionary, the analytic team identified 11.8% misclassification while the SAB identified 20.7% misclassification. Once each term dictionary was finalized, the LGBTQ+ term dictionary resulted in a 95% pairwise agreement, while the cancer term dictionary resulted in an 89.2% pairwise agreement. The classification tools developed by integrating community-engaged and technology-based methods were more accurate because of the equity-based approach of centering LGBTQ+ voices and their lived experiences. This exemplar suggests integrating community-engaged and technology-based methods to study inequities is highly feasible and has applications beyond LGBTQ+ financial burden research.

Comparative Analysis of Student Understanding Levels Using Lecture, Group Discussion and Information Technology- Based Methods of Postpartum Care Education at 'Aisyiyah University Surakarta

Postpartum care is one of the most essential subjects in midwifery program which student needs to obtain. This provides students with abilities based on concepts, attitudes, skills and the results of critical thinking as well as an evidence base in practice. This study aims to analyze the comparison of students' understanding levels using information technology-based, lecture and group discussion methods about postpartum care education at 'aisyiyah Surakarta University, especially during the Covid-19 pandemic. The method used was data collection ,form of interviews and questionnaires, related to midwifery care material/competencies using lecture, group discussion and information technology-based methods with a total of 37 students as respondents. Calculation the level of understanding using a Likert Scale, Validity Test (T-count, T-table) and Reliability Test, to find out the results of a comparison of learning models with lecture, group discussion and information technology-based methods. Results : The level of understanding using the lecture method is 81%, 94% in the group discussion method and 100% in information technology-based methods. Conclusion : It can be concluded that the learning model which is most in demand by students and has a strongly high level of comprehension was using information technology-based methods.

Aawn: An Interactive Mobile Application for Improving the Communication Skills of Arab Children with Autism

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that causes challenges in communication and social interaction. Since there is no single treatment for autism, autistic children need extra attention from their parents or caregivers to overcome their linguistic deficiency. Scientific studies have shown that technology-based educational methods are effective and can lead to a significant improvement, especially for autistic children. In recent years, an increasing number of mobile and multimedia applications have been developed to enhance autistic children's verbal communication, emotions, social behavior, and interaction skills. However, many of these systems are either in English or in local autistic children’s native languages. Others are designed to promote specific knowledge, i.e., emotions, or are limited in their features. This paper designs and implements a prototype for Arabic mobile application, called Aawn, to help and improve Arab autistic children's, in their own language, communication and emotions, as well as educational and organizational skills. Aawn is integrated with various supporting technologies based on the Picture Exchange Communication System (PECS) and augmented with graphical features. The system is built and developed using Android Studio and various cloud-based tools. The system can be extended by artificial intelligence (AI) technologies.

Smart vision-based analysis and error deduction of human pose to reduce musculoskeletal disorders in construction

PurposeThis pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.Design/methodology/approachUsing a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).FindingsResults show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.Research limitations/implicationsLiterature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.Practical implicationsThe theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.Social implicationsBy using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.Originality/valueHuman pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

Multi-scale adaptive multivariate state estimation fault detection enhancement for time-varying industrial system based on multi-output Gaussian process autoregression

Most chemical processes are time-varying and nonlinear due to load changes, product demand transitions or other causes, causing unsatisfactory performance of conventional non-parametric multivariate statistical fault detection method. In this work, a probabilistic multivariate state estimation fault detection method based on multi-output Gaussian process autoregression is first developed to overcome the linear limitation and noise information ignorance of multivariate state estimation technology-based fault detection methods. In multi-output Gaussian process regression framework, the Leave-One-Sample-Out strategy is developed to construct the dataset by leaving each historical sample from the memory matrix out as one training output in turn while regarding the corresponding remaining historical samples as one training input. Then, we design the multi-output Gaussian process autoregression model to estimate the current state of the system. Utilizing the estimation covariance information, a probabilistic index based on multivariate Kullback-Leibler divergence is developed for fault detection. Moreover, a multi-scale adaptive fault detection enhancement based on discrete multi-objective Archimedes optimization and just-in-time learning is further proposed to handle the time-varying problem. In this scheme, the memory matrix is batch-adaptively updated at monthly intervals based on discrete multi-objective Archimedes optimization to handle the slow change of system characteristics caused by equipment degradation. On the other hand, to cope with the rapid change of system characteristics caused by operation transition, the just-in-time learning is employed to select samples from the memory matrix that best match to the current system state for sample-adaptive updating. Finally, two industrial cases are used to verify the performance of the proposed method.

Anthropometric measures and physical examination could be used to assess phenotypic GLIM (Global leadership initiative on malnutrition) criteria in heart failure patients

Background and aimsThe assessment of muscle mass using technology-based methods is less commonly performed when applying the Global Leadership Initiative on Malnutrition (GLIM) criteria due to the lack of skilled clinical nutrition practitioners and/or equipment. Based on the predictive validity of poor health outcomes and feasibility in clinical practice, this study aimed to analyze whether the measurement of calf circumference (CC), mid-upper arm circumference (MAC), and the physical examination could be used as substitutes for muscle mass assessment, as well as handgrip strength (HGS) used as a substitution when applying the GLIM criteria in hospitalized HF patients. Methods and resultsFrom June 2022 to January 2023, a single-center prospective study including 216 patients was performed. Additionally, covariates were identified by a directed acyclic graph. The multivariate logistic regression analysis was also used to analyze and compare the association between poor health outcomes and malnutrition (based on 5 types of GLIM criteria). Cohen-kappa coefficient and TELOS-feasibility score were calculated. The prevalence of malnutrition ranged from 35.2% to 42.6%, depending on the tool used. After adjusting for covariates, malnutrition assessed using CC, MAC, or physical examination within the GLIM criteria was independently associated with poor clinical outcomes (90-day HF-related readmission or all-cause mortality and prolonged hospital stay) but not with HGS. ConclusionCC, MAC and results from physical examination but not HGS may serve as a substitutive metric of muscle mass contained in the GLIM criteria to diagnose malnutrition and predict poor clinical outcomes among HF patients. Registration numberThis study was registered at Chinese Clinical Trial Registry.(ChiCTR2200057876) on 20 Mar. 2022.

Development of a Google Earth Engine-Based Application for the Management of Shallow Coral Reefs Using Drone Imagery

The Caribbean is one of the world’s most vulnerable regions to the projected impacts of climate change, and changes in coral reef ecosystems have been studied over the last two decades. Lately, new technology-based methods using satellites and unmanned vehicles, among others have emerged as tools to aid the governance of these ecosystems by providing managers with high-quality data for decision-making processes. This paper addresses the development of a Google Earth Engine (GEE)-based application for use in the management processes of shallow coral reef ecosystems, using images acquired with Remotely Piloted Aircraft Systems (RPAS) known as drones, at the Old Providence McBean Lagoon National Natural Park; a Marine Protected Area (MPA) located northwest of Old Providence Island, Colombia. Image acquisition and processing, known as drone imagery, is first described for flights performed using an RTK multispectral drone at five different monitoring stations within the MPA. Then, the use of the GEE app is described and illustrated. The user executes four simple steps starting with the selection of the orthomosaics uploaded to GEE and obtaining the reef habitat classification for four categories: coral, macroalgae, sand, and rubble, at any of the five monitoring stations. Results show that these classes can be effectively mapped using different machine-learning (ML) algorithms available inside GEE, helping the manager obtain high-quality information about the reef. This remote-sensing application represents an easy-to-use tool for managers that can be integrated into modern ecosystem monitoring protocols, supporting effective reef governance within a digitized society with more demanding stakeholders.

Financial Technology with QRIS Payment System for Entrepreneurship Locker

The Covid-19 pandemic has an impact not only on health but also on human activities, one of which is economic transactions. A number of policies related to health protocols have caused limitations for the community in transacting with each other. In relation to economic transactions, entrepreneurial transactions on campus have stopped due to policies related to the pandemic. To answer this problem, an invention called "Culinary Business Automatic Service Locker (Entrepreneurship Locker)" that based on the Internet of Things that implements financial technology in its payment method was created. The implementation of Financial Technology is intended to revive entrepreneurship on campus by providing a “new user experience” to all parties involved in these activities. In recent years, financial technology as a new concept in payments has been growing. The concept of finance technology is to create a payment platform where there is no longer a need for physical interaction between the seller and the buyer, because the transaction process occurs via digital. QRIS, which stands for Quick Response Code Indonesia Standard is one of the financial technology-based payment methods that has been authorized in Indonesia. There are two types of QRIS, namely static QRIS and dynamic QRIS. In this study, the dynamic QRIS API will be used because it is able to generate different nominal and QR codes for different transaction. In addition, an e-wallet is needed for users to support payments by scanning the QR code via smartphone. This research wants to see how the application of financial technology using dynamic QRIS and e-wallet to entrepreneurial lockers. The results showed that financial technology using dynamic QRIS and e-wallets can be utilized in the automatic payment system for entrepreneurial lockers

Embedding Sustainable Mathematics Higher Education in the Fourth Industrial Revolution Era Post-COVID-19: Exploring Technology-Based Teaching Methods

Higher Education Institutions have adopted technology-based teaching methods to prevent the spreading of the contagious coronavirus (COVID-19). In the Fourth Industrial Revolution (4IR) era, technology-based teaching methods are indispensable for scaffolding teaching, learning and assessment. Mathematics is an important discipline in education, and provides a basis for problem solving, critical thinking and analytical skills, which is important to consider when focusing on sustainability. Thus, to add knowledge to the field about integrating technology-based teaching methods in mathematics, Higher Education environments during and post-COVID-19 need to be interrogated. This added knowledge is be valuable in the 4IR era post-COVID-19 for sustaining mathematics in Higher Education. This study explored participants’ experiences, views, implications and suggestions for technology-based teaching methods for mathematics. These participants (N = 45) were postgraduate students and mathematics school teachers at the research site in KwaZulu-Natal, South Africa. The research location for this qualitative study was a South African Higher Education Institution, and the study was conducted during the COVID-19 pandemic. The Community of Inquiry theoretical framework and the Substitution, Augmentation, Modification and Redefinition (SAMR) theoretical model guided this study. Participants were invited to two interactive online workshops. At these workshops, participants were introduced to different technology-based teaching methods. Then, they were invited to individual online interviews. The findings of this study suggest important experiences, views and suggestions for using technology-based teaching methods in Higher Education mathematics contexts in the 4IR era. These findings provide important implications and further research possibilities for embedding sustainable mathematics in Higher Education in the 4IR era, post-COVID-19.

A Teacher’s Guide to Technology-Based Self-Monitoring Strategies for Student Behavior

Students with disabilities may demonstrate high rates of off-task behavior, resulting in poor academic achievement. To decrease students’ off-task behavior, teachers can identify student-guided supportive strategies to limit the amount of time they dedicate to behavior management. Moreover, when teachers use effective student-guided strategies that reflect high social validity, ease of use, and low intrusiveness, benefits are maximized and students will maintain their use of the strategy. This article provides step-by-step procedures for designing a technology-based self-monitoring (TBSM) strategy that increases the acceptability and continued use of standard self-monitoring procedures. Necessary adjustments to typical self-monitoring strategies considering technology-based delivery methods, including selecting and evaluating mobile applications, are introduced.

Talent identification research: a bibliometric study from multidisciplinary and global perspectives.

This paper describes the general status, trends, and evolution of research on talent identification across multiple fields globally over the last 80 years. Using Scopus and Web of Science databases, we explored patterns of productivity, collaboration, and knowledge structures in talent identification (TI) research. Bibliometric analysis of 2,502 documents revealed talent identification research is concentrated in the fields of management, business, and leadership (~37%), sports and sports science (~20%), and education, psychology, and STEM (~23%). Whereas research in management and sports science has occurred independently, research in psychology and education has created a bridge for the pollination of ideas across fields. Thematic evolution analysis indicates that TI has well developed motor and basic research themes focused on assessment, cognitive abilities, fitness, and youth characteristics. Motor themes in management and sports science bring attention to talent management beyond TI. Emerging research focuses on equity and diversity as well as innovation in identification and technology-based selection methods. Our paper contributes to the development of the body of TI research by (a) highlighting the role of TI across multiple disciplines, (b) determining the most impactful sources and authors in TI research, and (c) tracing the evolution of TI research which identifies gaps and future opportunities for exploring and developing TI research and its broader implications for other areas of research and society.