Novi Andayani Praptiningsih, Herri Mulyono, B. Setiawan
This study set out to identify and analyze toxic relationships in interpersonal communication among adolescents. The toxic relationship, as an unhealthy relationship, does have an impact on the occurrence of internal conflicts. Such relationships often cause the people involved to encounter unproductiveness and mental disorders, which can trigger an emotional outburst that leads to violence. A qualitative approach was used as the research method. The data collection techniques comprised FGD, observation, and in-depth interviews with informants/participants as primary data. The study findings show that first, the perpetrators of toxic relationships, namely toxic people, could be those closest to the victims, such as the nuclear family (father, mother, and siblings). In addition, the perpetrator could be a lover in an unhealthy romantic relationship or peers and even friends who often do the bullying via verbal, physical, or even sexual violence. Second, toxic relationships can be categorized into several forms, namely unhealthy relationships with friends (‘toxic friendship’), parents/family (‘toxic parenting’), lovers, and cheating parents, which can affect a child’s mentality. Actions necessary include the raising of awareness and concern for the community. If violent behavior occurs, it is not permissible to act permissive. The individual approach carried out during victim assistance can entail consultations in the form of ‘vent sessions’. A powerful way to anticipate being trapped in an unhealthy relationship is via self-love. Counselling is carried out with a self-healing approach to restore victims’ self-confidence and maintain their mental health.
{"title":"Toxic relationship in youth communication through self-love intervention strategy","authors":"Novi Andayani Praptiningsih, Herri Mulyono, B. Setiawan","doi":"10.30935/ojcmt/14292","DOIUrl":"https://doi.org/10.30935/ojcmt/14292","url":null,"abstract":"This study set out to identify and analyze toxic relationships in interpersonal communication among adolescents. The toxic relationship, as an unhealthy relationship, does have an impact on the occurrence of internal conflicts. Such relationships often cause the people involved to encounter unproductiveness and mental disorders, which can trigger an emotional outburst that leads to violence. A qualitative approach was used as the research method. The data collection techniques comprised FGD, observation, and in-depth interviews with informants/participants as primary data. The study findings show that first, the perpetrators of toxic relationships, namely toxic people, could be those closest to the victims, such as the nuclear family (father, mother, and siblings). In addition, the perpetrator could be a lover in an unhealthy romantic relationship or peers and even friends who often do the bullying via verbal, physical, or even sexual violence. Second, toxic relationships can be categorized into several forms, namely unhealthy relationships with friends (‘toxic friendship’), parents/family (‘toxic parenting’), lovers, and cheating parents, which can affect a child’s mentality. Actions necessary include the raising of awareness and concern for the community. If violent behavior occurs, it is not permissible to act permissive. The individual approach carried out during victim assistance can entail consultations in the form of ‘vent sessions’. A powerful way to anticipate being trapped in an unhealthy relationship is via self-love. Counselling is carried out with a self-healing approach to restore victims’ self-confidence and maintain their mental health.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140357419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamad Saifudin Mohamad Saleh, Miao Huang, Ali Mehellou, Lei Wang
As future leaders, millennials are invariably expected to adopt sustainable behavior (SB) and contribute to achieving the 2030 sustainable development goals. The bulk of existing research on SB and young people have applied a west-centric lens that are not adequately comparative in nature. By adopting the dual approaches of quantitative study and planned behavior theory, this study therefore intended to compare two Asian countries’ Malaysia and China–millennials’ input on SB and to examine the moderating role of social media usage with regards to such behavior. An online questionnaire was administered to 419 respondents from Malaysia and 416 respondents from China. The data were analyzed using the partial least squares structural equation modelling (PLS-SEM). PLS-SEM results indicated that the direct effects between the variables, which included the impact of sustainable knowledge and interpersonal influence on attitude toward sustainability (ATS); the impact of ATS on sustainable intention (SI); and the impact of SI on SB in both models (Malaysia and China) were found to be significant with only a slight difference in the path coefficients between the two models. Interestingly, PLS-SEM results also discovered no moderating effect of social media usage in both Malaysia and China. The result of the study is helpful for policymakers in both countries to use as reference when focusing on vital elements, such as sustainability knowledge to promote SB among their respective millennials.
{"title":"Sustainable behavior among millennials in Malaysia and China: The moderating role of social media usage","authors":"Mohamad Saifudin Mohamad Saleh, Miao Huang, Ali Mehellou, Lei Wang","doi":"10.30935/ojcmt/14409","DOIUrl":"https://doi.org/10.30935/ojcmt/14409","url":null,"abstract":"As future leaders, millennials are invariably expected to adopt sustainable behavior (SB) and contribute to achieving the 2030 sustainable development goals. The bulk of existing research on SB and young people have applied a west-centric lens that are not adequately comparative in nature. By adopting the dual approaches of quantitative study and planned behavior theory, this study therefore intended to compare two Asian countries’ Malaysia and China–millennials’ input on SB and to examine the moderating role of social media usage with regards to such behavior. An online questionnaire was administered to 419 respondents from Malaysia and 416 respondents from China. The data were analyzed using the partial least squares structural equation modelling (PLS-SEM). PLS-SEM results indicated that the direct effects between the variables, which included the impact of sustainable knowledge and interpersonal influence on attitude toward sustainability (ATS); the impact of ATS on sustainable intention (SI); and the impact of SI on SB in both models (Malaysia and China) were found to be significant with only a slight difference in the path coefficients between the two models. Interestingly, PLS-SEM results also discovered no moderating effect of social media usage in both Malaysia and China. The result of the study is helpful for policymakers in both countries to use as reference when focusing on vital elements, such as sustainability knowledge to promote SB among their respective millennials.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Chinese Communist Party (CCP) utilizes strict censorship to enhance its legitimacy and justify its actions. In the digital age, the internet is a vital platform for disseminating propaganda to domestic and global audiences. Political cartoons transpire as a potent tool, employing parody to transmit political messages. Their effectiveness lies in their faculty to simplify complex ideas, provide humor, and reinforce biases. China’s diplomatic approach has shifted to wolf warrior diplomacy, a use of authoritative language to safeguard its interests. Chinese diplomats increasingly use X (formerly Twitter) to convey political messages, and growingly, anti-US sentiments through negative portrayals. This paper reviews the thematic relationship between tweets by the Chinese government and anti-US propaganda political cartoons, exploring how tweets from government officials influence the creation of negative portrayals of the US. Employing a content analysis methodology, the study explores tweets and political cartoons, revealing insights into China’s soft power and propaganda efforts. It was found that there is a significant correlation between anti-US sentiment expressed through tweets and political cartoons, with variations depending on specific categories of political subject matter and presidential administrations.
{"title":"Tweet wars: China's anti-US propaganda through political cartoons","authors":"Mitchell Gallagher","doi":"10.30935/ojcmt/14415","DOIUrl":"https://doi.org/10.30935/ojcmt/14415","url":null,"abstract":"The Chinese Communist Party (CCP) utilizes strict censorship to enhance its legitimacy and justify its actions. In the digital age, the internet is a vital platform for disseminating propaganda to domestic and global audiences. Political cartoons transpire as a potent tool, employing parody to transmit political messages. Their effectiveness lies in their faculty to simplify complex ideas, provide humor, and reinforce biases. China’s diplomatic approach has shifted to wolf warrior diplomacy, a use of authoritative language to safeguard its interests. Chinese diplomats increasingly use X (formerly Twitter) to convey political messages, and growingly, anti-US sentiments through negative portrayals. This paper reviews the thematic relationship between tweets by the Chinese government and anti-US propaganda political cartoons, exploring how tweets from government officials influence the creation of negative portrayals of the US. Employing a content analysis methodology, the study explores tweets and political cartoons, revealing insights into China’s soft power and propaganda efforts. It was found that there is a significant correlation between anti-US sentiment expressed through tweets and political cartoons, with variations depending on specific categories of political subject matter and presidential administrations.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Turkey has been struck by several powerful earthquakes. Since the 1999 earthquake was the most recent and devastating earthquake before the last one happened in February 2023, many of these media channels’ depictions of the 2023 earthquake in Turkey may have been impacted by the collective memory of the 1999 earthquake. Collective memory of disasters and conflicts frequently takes on special significance as a mechanism for society to cope with the catastrophic events they have witnessed. Collective memory aids societies in dealing with the consequences of such events by giving a feeling of continuity as well as a structure for interpreting and comprehending what occurred. The media and social media are important in developing and conveying collective memory. They play an important role in framing events, transmitting details, and providing a forum for public debate. Social media, in addition to traditional media, has emerged as an innovative platform for the construction and diffusion of collective memory. The purpose of this study is to investigate whether the Turkish media depicted the collective memory of the 1999 earthquake in the aftermath of the 2023 earthquake. If the collective memory of the 1999 earthquake is invoked in media coverage of the 2023 earthquake, how is it depicted in terms of lessons learned, public response, and influence on Turkish society? The study’s findings indicate that the analysis of Turkish media coverage pertaining to the 2023 earthquake has demonstrated a restricted collective recollection of the 1999 earthquake.
{"title":"Stimulation of the collective memory of the 1999 Turkey earthquake through the Turkish media coverage of the 2023 earthquake","authors":"Yasmin Aldamen, Dilana Thasleem Abdul Jaleel","doi":"10.30935/ojcmt/14407","DOIUrl":"https://doi.org/10.30935/ojcmt/14407","url":null,"abstract":"Turkey has been struck by several powerful earthquakes. Since the 1999 earthquake was the most recent and devastating earthquake before the last one happened in February 2023, many of these media channels’ depictions of the 2023 earthquake in Turkey may have been impacted by the collective memory of the 1999 earthquake. Collective memory of disasters and conflicts frequently takes on special significance as a mechanism for society to cope with the catastrophic events they have witnessed. Collective memory aids societies in dealing with the consequences of such events by giving a feeling of continuity as well as a structure for interpreting and comprehending what occurred. The media and social media are important in developing and conveying collective memory. They play an important role in framing events, transmitting details, and providing a forum for public debate. Social media, in addition to traditional media, has emerged as an innovative platform for the construction and diffusion of collective memory. The purpose of this study is to investigate whether the Turkish media depicted the collective memory of the 1999 earthquake in the aftermath of the 2023 earthquake. If the collective memory of the 1999 earthquake is invoked in media coverage of the 2023 earthquake, how is it depicted in terms of lessons learned, public response, and influence on Turkish society? The study’s findings indicate that the analysis of Turkish media coverage pertaining to the 2023 earthquake has demonstrated a restricted collective recollection of the 1999 earthquake.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research investigates the factors influencing consumers’ online buying behavior (OBB) through the examination of six hypotheses: attitude, perceived benefits and intention, subjective norms, cyberchondria, self-efficacy, and self-isolation intention. This study included 216 respondents in total. It was determined whether online purchasing behavior was valid using structural equation modelling. According to the study, every relationship is statistically significant and positive in orientation, highlighting the significance of these elements in determining consumers’ OBB. The impact of attitude, perceived benefits and intentions, subjective norms, and self-efficacy is consistent with earlier research on consumer behavior, highlighting the psychological factors influencing online purchasing decisions. The significant effects of cyberchondria also highlight the importance of health-related considerations in online purchasing decisions. The impact of self-isolation intention highlights how crucial outside factors, like the COVID-19 pandemic, are in influencing consumers’ online shopping behavior. The findings are significant as they provide detailed insights into the behavior of online shoppers in Malaysia, highlighting COVID-19’s impact and function of diverse demographics, potentially contributing to existing knowledge in the field of consumer behavior.
{"title":"Online purchases among consumers during the COVID-19 pandemic in Malaysia","authors":"A. Raman, Kai Hu","doi":"10.30935/ojcmt/14252","DOIUrl":"https://doi.org/10.30935/ojcmt/14252","url":null,"abstract":"This research investigates the factors influencing consumers’ online buying behavior (OBB) through the examination of six hypotheses: attitude, perceived benefits and intention, subjective norms, cyberchondria, self-efficacy, and self-isolation intention. This study included 216 respondents in total. It was determined whether online purchasing behavior was valid using structural equation modelling. According to the study, every relationship is statistically significant and positive in orientation, highlighting the significance of these elements in determining consumers’ OBB. The impact of attitude, perceived benefits and intentions, subjective norms, and self-efficacy is consistent with earlier research on consumer behavior, highlighting the psychological factors influencing online purchasing decisions. The significant effects of cyberchondria also highlight the importance of health-related considerations in online purchasing decisions. The impact of self-isolation intention highlights how crucial outside factors, like the COVID-19 pandemic, are in influencing consumers’ online shopping behavior. The findings are significant as they provide detailed insights into the behavior of online shoppers in Malaysia, highlighting COVID-19’s impact and function of diverse demographics, potentially contributing to existing knowledge in the field of consumer behavior.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140357362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Raúl Alberto García Castro, Gilber Chura-Quispe, Jehovanni Fabrizio Velarde Molina, Luis Alberto Espinoza Ramos, Catherine Alessandra Almonte Durand
The purpose of this article is to carry out an analysis of the disclosures made on teaching methods applying artificial intelligence in the Scopus database. The bibliometric review method was used to analyze 349 scientific articles dating from 1978 to 2023. The analysis was carried out using Bibliometrix and VOSviewer software, and the results show that from 2021 onwards there will be a notable increase in publications, with Mobile Information Systems being the journal with the highest production. Among 65 countries identified, China is the country with the highest production and the most productive organization was the Ministry of Education of the People’s Republic of China. No single author stands out for his or her highest scientific output, given that the maximum number of articles published per author is two. However, among the most cited authors is Alimisis, D. and the most co-cited author is Wang, Y. In terms of co-authorship, there is little contribution between authors, while collaboration between countries, China together with Hong Kong, Japan, Malaysia, Mexico, South Korea, Taiwan, Thailand form the most collaborative conglomerate. Cooperation between institutions, the division of computer engineering and the National University of Singapore, show the strongest collaboration. The strongest keywords are “artificial intelligence”, followed by “teaching methods” and “machine learning” and the topics that will be trending from 2021 onwards are “machine learning”, “ChatGPT”, “deep learning”.
{"title":"Bibliometric review on teaching methods with artificial intelligence in education","authors":"Raúl Alberto García Castro, Gilber Chura-Quispe, Jehovanni Fabrizio Velarde Molina, Luis Alberto Espinoza Ramos, Catherine Alessandra Almonte Durand","doi":"10.30935/ojcmt/14367","DOIUrl":"https://doi.org/10.30935/ojcmt/14367","url":null,"abstract":"The purpose of this article is to carry out an analysis of the disclosures made on teaching methods applying artificial intelligence in the Scopus database. The bibliometric review method was used to analyze 349 scientific articles dating from 1978 to 2023. The analysis was carried out using Bibliometrix and VOSviewer software, and the results show that from 2021 onwards there will be a notable increase in publications, with Mobile Information Systems being the journal with the highest production. Among 65 countries identified, China is the country with the highest production and the most productive organization was the Ministry of Education of the People’s Republic of China. No single author stands out for his or her highest scientific output, given that the maximum number of articles published per author is two. However, among the most cited authors is Alimisis, D. and the most co-cited author is Wang, Y. In terms of co-authorship, there is little contribution between authors, while collaboration between countries, China together with Hong Kong, Japan, Malaysia, Mexico, South Korea, Taiwan, Thailand form the most collaborative conglomerate. Cooperation between institutions, the division of computer engineering and the National University of Singapore, show the strongest collaboration. The strongest keywords are “artificial intelligence”, followed by “teaching methods” and “machine learning” and the topics that will be trending from 2021 onwards are “machine learning”, “ChatGPT”, “deep learning”.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The research study examines the usage of ChatGPT, an artificial intelligence (AI)-based language model, among media students in Egypt, focusing on the opportunities and challenges it presents. Through a survey, undergraduate media students shared their familiarity with ChatGPT, frequency of usage, and the media tasks performed using the tool. The study investigates the perceptions and experiences of undergraduate media students in Egypt about the benefits, challenges and implications of using ChatGPT for various aspects of media projects in their academic curriculum. It also examines the experiences of media students about content quality, creativity, organization of content, efficiency of expression, ethical concerns, and potential effects on authenticity and originality in media projects. The study adopted a mixed methods approach with a survey questionnaire and semi-structured interviews. The participants were media students belonging to three institutions in Egypt. Findings revealed ChatGPT’s utility as a valuable tool in various media tasks while highlighting its limitations and ethical considerations. The research offers media educators and professionals insights into using ChatGPT for media projects. It also raises specific issues that can benefit AI tool developers to meet academic rigor and transparency requirements.
{"title":"Exploring the use of ChatGPT among media students in Egypt: Opportunities and challenges","authors":"Amr Assad","doi":"10.30935/ojcmt/14416","DOIUrl":"https://doi.org/10.30935/ojcmt/14416","url":null,"abstract":"The research study examines the usage of ChatGPT, an artificial intelligence (AI)-based language model, among media students in Egypt, focusing on the opportunities and challenges it presents. Through a survey, undergraduate media students shared their familiarity with ChatGPT, frequency of usage, and the media tasks performed using the tool. The study investigates the perceptions and experiences of undergraduate media students in Egypt about the benefits, challenges and implications of using ChatGPT for various aspects of media projects in their academic curriculum. It also examines the experiences of media students about content quality, creativity, organization of content, efficiency of expression, ethical concerns, and potential effects on authenticity and originality in media projects. The study adopted a mixed methods approach with a survey questionnaire and semi-structured interviews. The participants were media students belonging to three institutions in Egypt. Findings revealed ChatGPT’s utility as a valuable tool in various media tasks while highlighting its limitations and ethical considerations. The research offers media educators and professionals insights into using ChatGPT for media projects. It also raises specific issues that can benefit AI tool developers to meet academic rigor and transparency requirements.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The pupillary responses of humans exhibit variations in size, which are mediated by optic and oculomotor cranial nerves. Due to their sensitivity and high resolution of pupillary responses, they are used for a long time as measurement metrics of cognitive effort. Investigating the extent of cognitive effort required during tasks of varying difficulty is crucial for understanding the neural interconnections underlying these pupillary responses. This study aims to assess human cognitive efforts involved in visually presented cognitive tasks using the multinomial processing tree (MPT) model, an analytical tool that disentangles and predicts distinct cognitive processes, resulting in changes in pupil diameter. To achieve this, a pupillary response dataset was collected during mental multiplication (MM) tasks and visual stimuli presentations as cognitive tasks. MPT model describes observed response frequencies across various response categories and determines the transition probabilities from one latent state to the next. The expectation maximization (EM) algorithm is employed with MPT model to estimate parameter values based on response frequency within each category. Both group-level and individual subject-to-subject comparisons are conducted to estimate cognitive effort. The results reveal that in the group comparison and with respect to task difficulty level, that subject’s knowledge on MM task influences the successfully solve the problem. Regarding individual analysis, no significant differences are observed in parameters related to correct recall, problem-solving ability, and time constraint compliance. However, some significant differences are found in parameters associated with the perceived difficulty level and ability to recall the correct answers. MPT model combined with EM algorithm constitutes a probabilistic model that enhances pupillary responses identification related to the cognitive effort. Potential applications of this model include disease diagnostics based on parameter values and identification of neural pathways that are involved in the pupillary response and subject’s cognitive effort. Furthermore, efforts are underway to connect this psychological model with an artificial neural network.
人类的瞳孔反应大小不一，由视神经和眼球运动颅神经介导。由于瞳孔反应的灵敏性和高分辨率，它们长期以来一直被用作认知努力的测量指标。调查不同难度任务中所需的认知努力程度对于了解这些瞳孔反应背后的神经互连至关重要。多叉处理树（MPT）模型是一种分析工具，它能分解和预测不同的认知过程，从而导致瞳孔直径的变化。为此，我们收集了心算乘法（MM）任务和视觉刺激呈现作为认知任务时的瞳孔反应数据集。MPT 模型描述了在各种反应类别中观察到的反应频率，并确定了从一个潜伏状态到下一个潜伏状态的过渡概率。期望最大化（EM）算法与 MPT 模型一起使用，根据每个类别中的反应频率来估计参数值。为了估算认知努力，我们进行了组间比较和受试者间比较。结果显示，在群体比较中，就任务难度而言，受试者对 MM 任务的了解程度会影响其成功解决问题的程度。在个体分析方面，与正确回忆、解决问题能力和遵守时间限制相关的参数没有发现显著差异。然而，在与感知难度水平和回忆正确答案的能力相关的参数方面，却发现了一些明显的差异。MPT 模型与 EM 算法相结合构成了一个概率模型，可增强与认知努力相关的瞳孔反应识别能力。该模型的潜在应用包括根据参数值进行疾病诊断，以及识别参与瞳孔反应和受试者认知努力的神经通路。此外，目前正在努力将这一心理模型与人工神经网络连接起来。
{"title":"Cognitive effort assessment through pupillary responses: Insights from multinomial processing tree modeling and neural interconnections","authors":"Gahangir Hossain, J. Elkins","doi":"10.30935/ojcmt/14196","DOIUrl":"https://doi.org/10.30935/ojcmt/14196","url":null,"abstract":"The pupillary responses of humans exhibit variations in size, which are mediated by optic and oculomotor cranial nerves. Due to their sensitivity and high resolution of pupillary responses, they are used for a long time as measurement metrics of cognitive effort. Investigating the extent of cognitive effort required during tasks of varying difficulty is crucial for understanding the neural interconnections underlying these pupillary responses. This study aims to assess human cognitive efforts involved in visually presented cognitive tasks using the multinomial processing tree (MPT) model, an analytical tool that disentangles and predicts distinct cognitive processes, resulting in changes in pupil diameter. To achieve this, a pupillary response dataset was collected during mental multiplication (MM) tasks and visual stimuli presentations as cognitive tasks. MPT model describes observed response frequencies across various response categories and determines the transition probabilities from one latent state to the next. The expectation maximization (EM) algorithm is employed with MPT model to estimate parameter values based on response frequency within each category. Both group-level and individual subject-to-subject comparisons are conducted to estimate cognitive effort. The results reveal that in the group comparison and with respect to task difficulty level, that subject’s knowledge on MM task influences the successfully solve the problem. Regarding individual analysis, no significant differences are observed in parameters related to correct recall, problem-solving ability, and time constraint compliance. However, some significant differences are found in parameters associated with the perceived difficulty level and ability to recall the correct answers. MPT model combined with EM algorithm constitutes a probabilistic model that enhances pupillary responses identification related to the cognitive effort. Potential applications of this model include disease diagnostics based on parameter values and identification of neural pathways that are involved in the pupillary response and subject’s cognitive effort. Furthermore, efforts are underway to connect this psychological model with an artificial neural network.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139786421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research explores the perceptions of Korean university students regarding artificial intelligence (AI)-based writing tools that include tools guided by machine learning, such as Google Translate and Naver Papago, and generative AI tools, such as Grammarly. A mixed methodology was used, including both quantitative and qualitative data. Among students who have taken English writing courses, 80 Korean university students volunteered for the online survey. After the survey, the research team recruited interview participants, and five volunteered participants joined the focus group interview. The study results indicate that these AI-based writing tools could improve English language learners (ELLs) writing skills. ELLs also noted the strengths and weaknesses of each AI-based tool, including the accessibility of translation machine learning and the error-checking capabilities of generative AI. However, interview data analysis indicates that the excessive use of AI-based writing tools could interfere with ELLs’ English writing process. This study highlights the need to effectively integrate AI-based tools in English language teaching for adult ELLs worldwide.
{"title":"University students’ perceptions of artificial intelligence-based tools for English writing courses","authors":"Yong-Jik Lee, Robert O. Davis, Sun Ok Lee","doi":"10.30935/ojcmt/14195","DOIUrl":"https://doi.org/10.30935/ojcmt/14195","url":null,"abstract":"This research explores the perceptions of Korean university students regarding artificial intelligence (AI)-based writing tools that include tools guided by machine learning, such as Google Translate and Naver Papago, and generative AI tools, such as Grammarly. A mixed methodology was used, including both quantitative and qualitative data. Among students who have taken English writing courses, 80 Korean university students volunteered for the online survey. After the survey, the research team recruited interview participants, and five volunteered participants joined the focus group interview. The study results indicate that these AI-based writing tools could improve English language learners (ELLs) writing skills. ELLs also noted the strengths and weaknesses of each AI-based tool, including the accessibility of translation machine learning and the error-checking capabilities of generative AI. However, interview data analysis indicates that the excessive use of AI-based writing tools could interfere with ELLs’ English writing process. This study highlights the need to effectively integrate AI-based tools in English language teaching for adult ELLs worldwide.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139846402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research explores the perceptions of Korean university students regarding artificial intelligence (AI)-based writing tools that include tools guided by machine learning, such as Google Translate and Naver Papago, and generative AI tools, such as Grammarly. A mixed methodology was used, including both quantitative and qualitative data. Among students who have taken English writing courses, 80 Korean university students volunteered for the online survey. After the survey, the research team recruited interview participants, and five volunteered participants joined the focus group interview. The study results indicate that these AI-based writing tools could improve English language learners (ELLs) writing skills. ELLs also noted the strengths and weaknesses of each AI-based tool, including the accessibility of translation machine learning and the error-checking capabilities of generative AI. However, interview data analysis indicates that the excessive use of AI-based writing tools could interfere with ELLs’ English writing process. This study highlights the need to effectively integrate AI-based tools in English language teaching for adult ELLs worldwide.
{"title":"University students’ perceptions of artificial intelligence-based tools for English writing courses","authors":"Yong-Jik Lee, Robert O. Davis, Sun Ok Lee","doi":"10.30935/ojcmt/14195","DOIUrl":"https://doi.org/10.30935/ojcmt/14195","url":null,"abstract":"This research explores the perceptions of Korean university students regarding artificial intelligence (AI)-based writing tools that include tools guided by machine learning, such as Google Translate and Naver Papago, and generative AI tools, such as Grammarly. A mixed methodology was used, including both quantitative and qualitative data. Among students who have taken English writing courses, 80 Korean university students volunteered for the online survey. After the survey, the research team recruited interview participants, and five volunteered participants joined the focus group interview. The study results indicate that these AI-based writing tools could improve English language learners (ELLs) writing skills. ELLs also noted the strengths and weaknesses of each AI-based tool, including the accessibility of translation machine learning and the error-checking capabilities of generative AI. However, interview data analysis indicates that the excessive use of AI-based writing tools could interfere with ELLs’ English writing process. This study highlights the need to effectively integrate AI-based tools in English language teaching for adult ELLs worldwide.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139786298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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