Search results

Researchers have previously utilized the project-based 6E learning model and the problem-based quantum learning model in various courses, such as the instructional principles and methods course and the character and values education course. These models were evaluated for their impact on students in different subjects, including developing skills, values, democracy perceptions, attitudes towards cooperative learning, metacognitive thinking skills and teacher self-efficacy perceptions. In 2023, Ökmen, Sahin and Kiliç reported positive outcomes, while Sahin and Kiliç reported similar findings in 2023a, 2023b and 2023c. There has been no investigation into how the models affect students' critical thinking and academic literacy. This study seeks to determine the impact of both models on these skills, gain more insight into their effectiveness and determine which is more beneficial. The results will guide the decision-making process for the character and values education course and other courses in the future. Specifically, this research aims to compare the effects of the project-based 6E learning model and problem-based quantum learning model on critical thinking and academic literacy.

This research employed the Solomon four-group experimental design to assess the efficacy of the applications. Prior knowledge and experience of the participants were evaluated through pretests. However, it should be noted that pretests may impact posttest scores either positively or negatively. For instance, participants taking the test multiple times may become more interested or attentive to the subject matter. The Solomon four-group design was deemed appropriate to analyze the influence of pretesting. This design enables the investigation of the application effect, pretest effect and interactive effect of pretest and application (van Engelenburg, 1999).

It was concluded that the project-based 6E learning model was effective in developing critical thinking in students, but not significantly. It was concluded that the problem-based quantum learning model significantly improved students' critical thinking skills. It was concluded at the end of the study that the project-based 6E learning model notably enhanced students' academic literacy. It was concluded that the problem-based quantum learning model had a significant positive impact on students' academic literacy. According to research, it has been determined that the problem-based quantum learning model is superior in enhancing critical thinking abilities compared to the project-based 6E learning model. Nevertheless, there seems to be no detectable disparity in the academic literacy advancement of pupils between the problem-based quantum learning model and the project-based 6E learning model.

There has been no investigation into how the models affect students' critical thinking and academic literacy. This study seeks to determine the impact of both models on these skills, gain more insight into their effectiveness and determine which is more beneficial. The results will guide the decision-making process for the character and values education course and other courses in the future.

Data literacy empowers college students, equipping them with essential skills necessary for their personal lives and careers in today’s data-driven world. This study aims to explore how community college students evaluate their data literacy and further examine demographic and educational/career advancement disparities in their self-assessed data literacy levels.

An online survey presenting a data literacy self-assessment scale was distributed and completed by 570 students at four community colleges. Statistical tests were performed between the data literacy factor scores and students’ demographic and educational/career advancement variables.

Male students rated their data literacy skills higher than females. The 18–19 age group has relatively lower confidence in their data literacy scores than other age groups. High school graduates do not feel proficient in data literacy to the level required for college and the workplace. Full-time employed students demonstrate more confidence in their data literacy than part-time and nonemployed students.

Given the lack of research on community college students’ data literacy, the findings of this study can be valuable in designing and implementing data literacy training programs for different groups of community college students.

This research aims to reveal the working principles of the decision mechanism that affects the use of neural implant acceptance and to discuss the leading role of digital literacy in this mechanism. In addition, it aimed to examine the theoretical connections of the research model with the conservation of resources (COR) and technology acceptance model (TAM) theories in the discussion.

The authors collected data from 300 individuals in an organization operating in the health sector and analyzed the data in the Smart Partial Least Squares (PLS) 3.3.3. This way, the authors determined the relationships between the variables, the path coefficients and the significance levels.

The study has found that strong digital literacy skills are linked to positive emotions and attitudes. Additionally, maintaining a positive mindset can improve one's understanding of ethics. Ethical attitudes and positive emotions can also increase the likelihood of adopting neural implants. Therefore, it is crucial to consider both technical and ethical concerns and emotions when deciding whether to use neural implants.

The research results determined the links between the cognitive, emotional and ethical factors in the cyborgization process of the employees and gave original insights to the managers and employees.

1. Determination of antecedents that affect individuals' acceptance of neural implant use.

2. Application to 300 individuals working in a health organization.

3. Path analysis using the least squares method via Smart PLS 3.3.3

4. Significant path coefficients among digital literacy, positive emotions, attitude, ethical understanding and acceptance of neural implant use.

Determination of antecedents that affect individuals' acceptance of neural implant use.

Application to 300 individuals working in a health organization.

Path analysis using the least squares method via Smart PLS 3.3.3

Significant path coefficients among digital literacy, positive emotions, attitude, ethical understanding and acceptance of neural implant use.

This paper aims to explore how critical digital and data literacies are facilitated by testing different methods in the classroom, with the ambition to find a pedagogical framework for prompting sustained critical literacies.

This contribution draws on a 10-year set of critical pedagogy experiments conducted in Denmark, USA and Italy, and engaging more than 1,500 young adults. Multi-method pedagogical design trains students to conduct self-oriented guided autoethnography, situational analysis, allegorical mapping, and critical infrastructure analysis.

The techniques of guided autoethnography for facilitating sustained data literacy rely on inviting multiple iterations of self-analysis through sequential prompts, whereby students move through stages of observation, critical thinking, critical theory-informed critique around the lived experience of hegemonic data and artificial intelligence (AI) infrastructures.

Critical digital/data literacy researchers should continue to test models for building sustained critique that not only facilitate changes in behavior over time but also facilitate citizen social science, whereby participants use these autoethnographic techniques with friends and families to build locally relevant critique of the hegemonic power of data/AI infrastructures.

The proposed literacy model adopts a critical theory stance and shows the value of using multiple modes of intervention at micro and macro levels to prompt self-analysis and meta-level reflexivity for learners. This framework places critical theory at the center of the pedagogy to spark more radical stances, which is contended to be an essential step in moving students from attitudinal change to behavioral change.

The purpose of this paper is to provide a transcript of a dialogue among literacy educators and researchers on the impact of generative aritficial intelligence (AI) in the field. In the spring of 2023, a lively conversation emerged on the National Council of Research on Language and Literacy (NCRLL)’s listserv. Stephanie initiated the conversation by sharing an op-ed she wrote for Atlanta Journal-Constitution about the rise of ChatGPT and similar generative AI platforms, moving beyond the general public’s concerns about student cheating and robot takeovers. NCRLL then convened a webinar of eight leading scholars in writing and literacies development, inspired by that listerv conversation and an organizational interest in promoting intergenerational collaboration among literacy scholars.

As former doctoral students of two of the panel participants, webinar facilitators Grace and Victoria positioned themselves primarily as learners about this topic and gathered questions from colleagues, P-16 practitioners and those outside the field of education to assess the concerns and wonderings that ChatGPT and generative AI have raised. The following webinar conversation was recorded on two different days due to scheduling conflicts. It has been merged and edited into one dialogue for coherence and convergence.

Panel participants raise a host of questions and issues that go beyond topics of ethics, morality and basic writing instruction. Furthermore, in dialogue with one another, they describe possibilities for meaningful pedagogy and critical literacy to ensure that generative AI is used for a socially just future for students. While the discussion addressed matters of pedagogy, definitions of literacy and the purpose of (literacy) education, other themes included a critique of capitalism; an interrogation of the systems of power and oppression involved in using generative AI; and the philosophical, ontological, ethical and practical life questions about being human.

This paper provides a glimpse into one of the first panel conversations about ChatGPT and generative AI in the field of literacy. Not only are the panel members respected scholars in the field, they are also former doctoral students and advisors of one another, thus positioning all involved as both learners and teachers of this new technology.

This study was carried out to examine the volume and annual growth pattern of research on e-health literacy research, investigate the open-access types of e-health literacy research and perform document production by country and by sources. The study also mapped the keywords used by authors to represent e-health literacy research and performed an analysis of the clusters of the keywords to reveal the thematic focus of research in the area.

The research was guided by a bibliometric approach involving visualization using VosViewer. Data were sourced from Scopus database using a syntax that was tested and verified to be capable of yielding reliable data on the subject matter. The analysis in this study was based on bibliographic data and keywords.

A total number of 1,176 documents were produced during 2006 and 2022. The majority of the documents (18.90%) were published based on hybrid open-access processes, and the USA has the highest contributions. The Journal of Medical Internet Research is the venue for most of the documents on the subject. The 1,176 documents were described by 5,047 keywords, 4.29 keywords per document, and the keywords were classified into five clusters that aptly capture the thematic structure of research in the area.

e-Health literacy has experienced significant growth in research production from 2006 to 2022, with an average of 69 documents per year. Research on e-health literacy initially had low output but began to increase in 2018. The majority of e-health literacy documents are available through open access, with the USA being the leading contributor. The analysis of keywords reveals the multifaceted nature of e-health literacy, including access to information, attitudes, measurement tools, awareness, age factors and communication. Clusters of keywords highlight different aspects of e-health literacy research, such as accessibility, attitudes, awareness, measurement tools and the importance of age, cancer, caregivers and effective communication in healthcare.

This study has practical implications for health promotion. There is also the element of patient empowerment in which case patients are allowed to take an active role in their healthcare. By understanding their health information and having access to resources that help them manage their conditions, patients can make informed decisions about their healthcare. Finally, there is the issue of improved health outcomes which can be achieved by improving patients' e-health literacy. Visualisation of e-health literacy can help bridge the gap between patients and healthcare providers, promote patient-centered care and improve health outcomes.

Research production on e-Health literacy has experienced significant growth from 2006 to 2022, with an average of 69 documents per year. Many e-health literacy documents are available through open access, and the USA is the leading contributor. The analysis of keywords reveals the nature of e-health literacy, including access to information, attitudes, measurement tools, awareness and communication. The clusters of keywords highlight different aspects of e-health literacy research, such as accessibility, attitudes, awareness, measurement tools and the importance of age, cancer, caregivers, and effective communication in healthcare.

With the rapid advancement of generative artificial intelligence (AI), it is important to consider how young people are making sense of these tools in their everyday lives. Drawing on critical postdigital approaches to learning and literacy, this study aims to center the experiences and perspectives of young people who encounter and experiment with generative AI in their daily writing practices.

This critical case study of one digital platform – Character.ai – brings together an adolescent and adult authorship team to inquire about the intertwining of young people’s playful and critical perspectives when writing on/with digital platforms. Drawing on critical walkthrough methodology (Light et al., 2018), the authors engage digital methods to study how the creative and “fun” uses of AI in youths’ writing lives are situated in broader platform ecologies.

The findings suggest experimentation and pleasure are key aspects of young people’s engagement with generative AI. The authors demonstrate how one platform works to capitalize on these dimensions, even as youth users engage critically and artfully with the platform and develop their digital writing practices.

This study highlights how playful experimentation with generative AI can engage young people both in pleasurable digital writing and in exploration and contemplation of platforms dynamics and structures that shape their and others’ literate activities. Educators can consider young people’s creative uses of these evolving technologies as potential opportunities to develop a critical awareness of how commercial platforms seek to benefit from their users.

This study contributes to the development of a critical and humanist research agenda around generative AI by centering the experiences, perspectives and practices of young people who are underrepresented in the burgeoning research devoted to AI and literacies.

Scholarship on America’s K-12 economics curriculum reveals an inattention to many harmful economic realities, specifically wealth inequality. Critics of the present curriculum posit that its emphasis on out-dated concepts and models ignores crucial elements of reality that impact economic interaction and identities. In response to the dominant economic paradigm and methods, this practitioner-focused paper discusses an economically pluralist, pedagogically critical approach to interrogating destructive economic realities. It details how three social studies classroom simulations based on the board game Monopoly may be integrated with certain informational texts to explore economic factors that contribute to America’s unique form of wealth inequality.

This paper describes wealth inequality in America and rationalizes the need to make this social problem a focus of study in the secondary social studies classroom. First, I survey the present curricular apparatus of K-12 economics education and then argue for a pluralist approach that expands the curriculum’s dominant neoclassical paradigm. Connecting economic pluralism to critical citizen education, I draw upon emerging critical economic citizen education scholarship to explain attendant pedagogical and instructional approaches. The described lesson builds upon a tradition of Monopoly simulations, is rooted in critical citizen education pedagogy and aligns with Soroko’s (2023) critical economic literacy framework.

This paper progresses the curricular movement of economic pluralism through its critique of America’s current K-12 economics curriculum that does not focus on immediate, lived social problems. It further defines critical economics, citizenship and pedagogy, then details an instructional practice that employs critical disciplinary tools to investigate contributing factors of American wealth inequality.

This paper contributes to the growing field of pluralist economic perspectives and pedagogies. Specifically, it enriches understanding of critical economics citizenship education by further defining attendant pedagogy and explaining Monopoly as an instructional tool for critical economics citizen education. Previous works have discussed Monopoly’s utility for teaching various concepts within the social studies disciplines. This simulation lesson is unique in its instructional approach that merges simulation experiences with certain informational texts to cultivate critical economic knowledge of American wealth inequality and critical economic skills for critiquing and transforming oppressive economic realities.