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Inquiry Frameworks for Research Question Scoping in DSR: A Realization for ChatGPT
Abstract
Research Question (RQ) Scoping refers to defining and refining a research question before conducting research. This step is crucial for ensuring the relevance and focus of the study, particularly in Design Science Research (DSR), where problems and solutions develop gradually. Literature reviews are a traditional method for comprehending the problem and determining key questions; however, they can be time-consuming and not worth it at the onset when lashing out in the dark. NLP chatbots such as ChatGPT can serve as a cost-effective alternative to clearing the way due to their capability to interact with users in a natural language-based manner and provide intuitive responses. The requirements for RQ Scoping extend beyond conversational support to include a framework for a sustained and iterative scoping process. An inquiry framework is necessary to guide and assist students and supervisors in fully harnessing the potential of NLP chatbots. This work incorporates ChatGPT into an inquiry framework for RQ Scoping, with mind maps as the visualization and the 5 Why technique as the inquiry strategy. Contributions include Design Principles, an IT artifact, and a Technology Acceptance Model evaluation (n = 9). Regarding perceived usefulness, the results indicate agreement on the intervention’s effectiveness in maintaining focus. However, there is less enthusiasm for mind maps as a communication tool. Perceived ease of use was also positive but revealed concerns about the query templates used by the framework.KeywordsRQ ScopingChatbotChatGPTMind maps
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Chat GPT, powered by the advanced GPT-3 language model from OpenAI, has reached 1 million users only in 5 days. Facebook, Netflix, Instagram, and Twitter could reach this number in 300, 1200, 75, and 720 days. With 175 billion parameters, GPT-3 can generate writing that closely resembles human language. Chat GPT can engage in multiple ongoing conversations, understand and respond to natural language input, and offer customized and interactive assistance. This makes Chat GPT a promising tool for open education, as it can improve the independence and autonomy of autodidactic learners, while also being both practical and adaptable. By providing personalized support, direction, and feedback, Chat GPT has the potential to increase motivation and engagement among autodidactic learners.
Artificial intelligence (AI) and computational sciences have aroused a growing interest in education. Despite its relatively recent history, AI is increasingly being introduced into the classroom through different modalities, with the aim of improving student achievement. Thus, the purpose of the research is to analyse, quantitatively and qualitatively, the impact of AI components and computational sciences on student performance. For this purpose, a systematic review and meta-analysis have been carried out in WOS and Scopus databases. After applying the inclusion and exclusion criteria, the sample was set at 25 articles. The results support the positive impact that AI and computational sciences have on student performance, finding a rise in their attitude towards learning and their motivation, especially in the STEM (Science, Technology, Engineering, and Mathematics) areas. Despite the multiple benefits provided, the implementation of these technologies in instructional processes involves a great educational and ethical challenge for teachers in relation to their design and implementation, which requires further analysis from the educational research. These findings are consistent at all educational stages.
p>Engineering education is constantly evolving to keep up with the latest technological developments and meet the changing needs of the engineering industry. One promising development in this field is the use of generative artificial intelligence technology, such as the ChatGPT conversational agent. ChatGPT has the potential to offer personalized and effective learning experiences by providing students with customized feedback and explanations, as well as creating realistic virtual simulations for hands-on learning. However, it is important to also consider the limitations of this technology. ChatGPT and other generative AI systems are only as good as their training data and may perpetuate biases or even generate and spread misinformation. Additionally, the use of generative AI in education raises ethical concerns such as the potential for unethical or dishonest use by students and the potential unemployment of humans who are made redundant by technology. While the current state of generative AI technology represented by ChatGPT is impressive but flawed, it is only a preview of what is to come. It is important for engineering educators to understand the implications of this technology and study how to adapt the engineering education ecosystem to ensure that the next generation of engineers can take advantage of the benefits offered by generative AI while minimizing any negative consequences.</p
Chatbots are increasingly becoming important gateways to digital services and information—taken up within domains such as customer service, health, education, and work support. However, there is only limited knowledge concerning the impact of chatbots at the individual, group, and societal level. Furthermore, a number of challenges remain to be resolved before the potential of chatbots can be fully realized. In response, chatbots have emerged as a substantial research area in recent years. To help advance knowledge in this emerging research area, we propose a research agenda in the form of future directions and challenges to be addressed by chatbot research. This proposal consolidates years of discussions at the CONVERSATIONS workshop series on chatbot research. Following a deliberative research analysis process among the workshop participants, we explore future directions within six topics of interest: (a) users and implications, (b) user experience and design, (c) frameworks and platforms, (d) chatbots for collaboration, (e) democratizing chatbots, and (f) ethics and privacy. For each of these topics, we provide a brief overview of the state of the art, discuss key research challenges, and suggest promising directions for future research. The six topics are detailed with a 5-year perspective in mind and are to be considered items of an interdisciplinary research agenda produced collaboratively by avid researchers in the field.
Artificial Intelligence (AI) are a wide-ranging set of technologies that promise several advantages for organizations in terms off added business value. Over the past few years, organizations are increasingly turning to AI in order to gain business value following a deluge of data and a strong increase in computational capacity. Nevertheless, organizations are still struggling to adopt and leverage AI in their operations. The lack of a coherent understanding of how AI technologies create business value, and what type of business value is expected, therefore necessitates a holistic understanding. This study provides a systematic literature review that attempts to explain how organizations can leverage AI technologies in their operations and elucidate the value-generating mechanisms. Our analysis synthesizes the current literature and highlights: (1) the key enablers and inhibitors of AI adoption and use; (2) the typologies of AI use in the organizational setting; and (3) the first- and second-order effects of AI. The paper concludes with an identification of the gaps in the literature and develops a research agenda that identifies areas that need to be addressed by future studies.
An increasing number of German schools have suspended teacher-directed learning (TL) in favor of self-directed learning (SL) modules. We used the broaden-and-build theory and self-determination theory as a theoretical framework to determine whether students in self-directed and teacher-directed learning environments differ in the interplay of positive emotions and learning strategies of students in secondary education. The study also compares the mediating role of autonomy support on the relationship between positive emotions and learning strategies. Questionnaire data from 787 German secondary school students in the sixth and seventh grades were analyzed. The results of the latent mean comparison indicated that students in the self-directed learning environment demonstrated more adaptive learning behaviors. Further, a multigroup structural equation model identified strong differences in the interplay of the variables between students in the self-directed and teacher-directed learning environments. In the teacher-directed learning environment, autonomy support was not found to mediate the relationship between positive emotions and learning strategies.
The purpose of this article is to explore a model of learning that proposes that various learning strategies are powerful at certain stages in the learning cycle. The model describes three inputs and outcomes (skill, will and thrill), success criteria, three phases of learning (surface, deep and transfer) and an acquiring and consolidation phase within each of the surface and deep phases. A synthesis of 228 meta-analyses led to the identification of the most effective strategies. The results indicate that there is a subset of strategies that are effective, but this effectiveness depends on the phase of the model in which they are implemented. Further, it is best not to run separate sessions on learning strategies but to embed the various strategies within the content of the subject, to be clearer about developing both surface and deep learning, and promoting their associated optimal strategies and to teach the skills of transfer of learning. The article concludes with a discussion of questions raised by the model that need further research.
Inquiry-based learning is gaining popularity in science curricula, international research and development projects as well as teaching. One of the underlying reasons is that its success can be significantly improved due to the recent technical developments that allow the inquiry process to be supported by electronic learning environments. Inquiry-based learning is often organized into inquiry phases that together form an inquiry cycle. However, different variations on what is called the inquiry cycle can be found throughout the literature. The current article focuses on identifying and summarizing the core features of inquiry-based learning by means of a systematic literature review and develops a synthesized inquiry cycle that combines the strengths of existing inquiry-based learning frameworks. The review was conducted using the EBSCO host Library; a total of 32 articles describing inquiry phases or whole inquiry cycles were selected based on specific search criteria. An analysis of the articles resulted in the identification of five distinct general inquiry phases: Orientation, Conceptualization, Investigation, Conclusion, and Discussion. Some of these phases are divided into sub-phases. In particular, the Conceptualization phase is divided into two (alternative) sub-phases, Questioning and Hypothesis Generation; the Investigation phase is divided into three sub-phases, Exploration or Experimentation leading to Data Interpretation; and the Discussion phase is divided into two sub-phases, Reflection and Communication. No framework bringing together all of these phases and sub-phases was found in the literature. Thus, a synthesized framework was developed to describe an inquiry cycle in which all of these phases and sub-phases would be present. In this framework, inquiry-based learning begins with Orientation and flows through Conceptualization to Investigation, where several cycles are possible. Inquiry-based learning usually ends with the Conclusion phase. The Discussion phase (which includes Communication and Reflection) is potentially present at every point during inquiry-based learning and connects to all the other phases, because it can occur at any time during (discussion in-action) or after inquiry-based learning when looking back (discussion on-action).
The Biomind program is a new open inquiry program for Israeli biology high school students. The Biomind program is facilitated
by diverse activities of asynchronous on-line forums for teachers and students. This research aims to analyse the discussions
that occurred over a period of three years in these forums, in order to obtain a picture of the benefits that virtual discussions
hold for the implementation of the open inquiry program. The results presented in this article indicate that students required
assistance mainly with searching scientific information, finding experimental techniques and procedures, and phrasing inquiry
questions. The three most frequent areas that were discussed in the teachers' forum were technical and procedural aspects
of experimentation, bureaucracy and phenomenon identification. In addition, issues such as inferring and discussing, logical
progression of the inquiry process, scientific writing, teacher-student interaction, reflective thinking, affective points
of view, and forum administration were raised in the forum discourses. The forum discourses create a learning community that
contributes to the implementation of the Biomind program, and pinpoint the aspects that should be taken into consideration
in the future.
This book provides guidelines for practicing design science in the fields of information systems and software engineering research. A design process usually iterates over two activities: first designing an artifact that improves something for stakeholders and subsequently empirically investigating the performance of that artifact in its context. This validation in context is a key feature of the book - since an artifact is designed for a context, it should also be validated in this context.
This book is an introductory text on design science, intended to support both graduate students and researchers in structuring, undertaking and presenting design science work. It builds on established design science methods as well as recent work on presenting design science studies and ethical principles for design science, and also offers novel instruments for visualizing the results, both in the form of process diagrams and through a canvas format. While the book does not presume any prior knowledge of design science, it provides readers with a thorough understanding of the subject and enables them to delve into much deeper detail, thanks to extensive sections on further reading. Design science in information systems and technology aims to create novel artifacts in the form of models, methods, and systems that support people in developing, using and maintaining IT solutions. This work focuses on design science as applied to information systems and technology, but it also includes examples from, and perspectives of, other fields of human practice. Chapter 1 provides an overview of design science and outlines its ties with empirical research. Chapter 2 discusses the various types and forms of knowledge that can be used and produced by design science research, while Chapter 3 presents a brief overview of common empirical research strategies and methods. Chapter 4 introduces a methodological framework for supporting researchers in doing design science research as well as in presenting their results. This framework includes five core activities, which are described in detail in Chapters 5 to 9. Chapter 10 discusses how to communicate design science results, while Chapter 11 compares the proposed methodological framework with methods for systems development and shows how they can be combined. Chapter 12 discusses how design science relates to research paradigms, in particular to positivism and interpretivism. Lastly, Chapter 13 discusses ethical issues and principles for design science research. © Springer International Publishing Switzerland 2014. All rights are reserved.
Science education reform documents emphasize the importance of inquiry experiences for young learners. This means that teachers must be prepared with the knowledge, skills, and habits of thinking to mentor their students through authentic investigations. This study examines how preservice teachers' inquiry experiences, in a science methods course, influenced and were influenced by their conceptions of inquiry. The study also assesses how these experiences were associated with eventual classroom practice. Six preservice secondary teachers were observed during a 2-month inquiry project and then followed into the classroom as they began a 9-week teaching practicum. Data revealed that participants' preproject conceptions of the inquiry process were related to the conduct and interpretation of their own inquiry project, and that the project experience modified the inquiry conceptions of those participants who already had sophisticated understandings of scientific investigations. Perhaps most importantly, the participants who eventually used guided and open inquiry during their student teaching were not those who had more authentic views of inquiry or reflected most deeply about their own inquiry projects, but rather they were individuals who had significant undergraduate or professional experiences with authentic science research. Finally, this article advocates that independent science investigations be part of preservice education and that these experiences should be scaffolded to prompt reflection specifically about the nature of inquiry and conceptually linked to ways in which inquiry can be brought into the K-12 classroom. © 2002 Wiley Periodicals, Inc. Sci Ed87:112–143, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/sce.10044
ContextThe technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of behavioural intention to use (BI) rather than actual usage.ObjectiveThis review examines the evidence that the TAM predicts actual usage using both subjective and objective measures of actual usage.MethodWe performed a systematic literature review based on a search of six digital libraries, along with vote-counting meta-analysis to analyse the overall results.ResultsThe search identified 79 relevant empirical studies in 73 articles. The results show that BI is likely to be correlated with actual usage. However, the TAM variables perceived ease of use (PEU) and perceived usefulness (PU) are less likely to be correlated with actual usage.ConclusionCare should be taken using the TAM outside the context in which it has been validated.
Abstract This study proposes a web-based collaborative inquiry learning system. This system uses the World-wide web (WWW) as a source of knowledge exploration, and provides exploratory problems to guide students to think and explore. A concept map is used as a tool of anchoring and representing knowledge during inquiry process. In the process of learning, learners are allowed to exchange the evidence they have collected, their personal opinions, and the concept maps that they have built. In order to effectively integrate the inquiry learning, collaborative learning, and concept map in the system, this study proposes a collaborative inquiry learning model and related learning activities. Two studies were constructed based on the collaborative inquiry learning model to investigate students' learning processes in the collaborative inquiry learning on the web.
The notion of scaffolding learners to help them succeed in solving problems otherwise too difficult for them is an important idea that has extended into the design of scaffolded software tools for learners. However, although there is a growing body of work on scaffolded tools, scaffold design, and the impact of scaffolding, the field has not yet converged on a common theoretical framework that defines rationales and approaches to guide the design of scaffolded tools. In this article, we present a scaffolding design framework addressing scaffolded software tools for science inquiry. Developed through iterative cycles of inductive and theory-based analysis, the framework synthesizes the work of prior design efforts, theoretical arguments, and empirical work in a set of guidelines that are organized around science inquiry practices and the challenges learners face in those practices. The framework can provide a basis for developing a theory of pedagogical support and a mechanism to describe successful scaffolding approaches. It can also guide design, not in a prescriptive manner but by providing designers with heuristics and examples of possible ways to address the challenges learners face.
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