DCLA13

The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic analysis, select, modify and compare texts of various types and genres. The purpose of this article and the journal issue as a whole is to present modern areas of research in computational linguistics and linguistic complexology, as well as to define a solid rationale for the new interdisciplinary field, i.e. discourse complexology. The review of trends in computational linguistics focuses on the following aspects of research: applied problems and methods, computational linguistic resources, contribution of theoretical linguistics to computational linguistics, and the use of deep learning neural networks. The special issue also addresses the problem of objective and relative text complexity and its assessment. We focus on the two main approaches to linguistic complexity assessment: “parametric approach” and machine learning. The findings of the studies published in this special issue indicate a major contribution of computational linguistics to discourse complexology, including new algorithms developed to solve discourse complexology problems. The issue outlines the research areas of linguistic complexology and provides a framework to guide its further development including a design of a complexity matrix for texts of various types and genres, refining the list of complexity predictors, validating new complexity criteria, and expanding databases for natural language.

University of Tennessee Graduate School of Medicine, Knoxville, Tennessee. dbustama@utmck.eduCore Clinical Competencies in Anesthesiology: A Case-based Approach. Edited by Christopher J. Gallagher, M.D., Michael C. Lewis, M.D., Deborah A. Schwengel, M.D. New York, Cambridge University Press, 2010. Pages: 486. Price: $85.00.How do the Accreditation Council for Graduate Medical Education (ACGME) core competencies apply to the daily practice of anesthesiology? What are these competencies anyway? What are they good for? Can you list them? Can you define each of the six core competencies? These are questions that regularly face anesthesiology residents, anesthesiology residency programs, and anesthesiology faculty members who endeavor to teach in a “competency-based” manner. Core Clinical Competencies in Anesthesiology: A Case-based Approach , edited by three anesthesiology residency program directors, was written to address these questions specifically.This softbound book begins by introducing the six ACGME core competencies: patient care, medical knowledge, practice-based learning and improvement, interpersonal and communication skills, professionalism, and systems-based practice. Next, the competencies are expounded upon and then related specifically to the learning and practice of anesthesiology. With the competency framework defined, the reader is launched directly into the 77 case reports, divided into 6 sections, which comprise the remainder of the book. Three of the six sections consist of cases contributed by the editors' own anesthesiology programs, Stony Brook University, University of Miami-Miller School of Medicine, and Johns Hopkins Medical Institutions. Contributions from the University of Medicine and Dentistry of New Jersey, the University of Texas M. D. Anderson Cancer Center, and the Medical College of Wisconsin form the remaining three sections. Although the cases are contributed by multiple authors from different institutions, they are presented using a fairly consistent format. Each case is presented concisely with a discussion directed at exploring the core competencies. Although some cases focus only on the competencies that are most applicable to the particular clinical situation, most examine each of the six core competencies.The tone is humorous, often irreverent. The writing style is conversational, having more in common with a collegial discussion than with a formal case report. The cases are self-contained such that each chapter can be read either independently or in any order without lessening the educational experience. Anesthesiologists and anesthesiology residents will find much to identify with in many of the 77 clinical situations contained here. Although the style is casual and humor is often present, the focus always remains sharply on learning and applying the core competencies. Each case report is carefully dissected, and elements of the anesthetic management are placed within the structure of the six competencies. This consistent examination of the core competencies leads to some repetition but adds emphasis to their application to anesthesiology education.A degree of ambiguity certainly exists in the structure of the core competencies. Some elements of clinical practice fall neatly into one of the competency categories. As a result, some elements are repeated several times throughout the book to illustrate a specific competency. Avoiding discussion of patients where it is possible to be overheard, for example, is frequently cited as an element of professionalism. Similarly, timely administration of prophylactic antibiotics fits well with the patient care competency and the competency language “provide health-care services aimed at preventing health problems or maintaining health.” In contrast, other behaviors are shown to fall under multiple categories. Hand washing is variously used as an example for the competencies of patient care, practice-based learning and improvement, interpersonal and communication skills, and professionalism. The challenging nature of the included cases and the humor in the presentations serve to keep the reader engaged during the process of conforming clinical situations in anesthesiology to the structure of the ACGME core competencies. Because the book is focused so intensely on the competencies, one is sometimes left wanting for further medical information, details of the anesthetic management, or clinical outcome related to a specific case. After a thorough reading, a reader is unlikely to have difficulty remembering the competencies or applying them to clinical situations.Many of the cases presented are unusual, interesting, educational, and challenging. One particularly memorable case is presented in chapter 10. The author recounts his experience with a patient who suffered total body burns, which unfortunately resulted in death. The role the author took in caring for this patient during the last hours before death illustrates, much more clearly than competency-based language, what professionalism means.Core Clinical Competencies in Anesthesiology: A Case-based Approach was written to assist those of us who have difficulty grasping the competencies, specifically those who have difficulty defining and applying the ACGME core competencies to the learning, teaching, and practice of anesthesiology. The book is targeted primarily at those involved in anesthesiology education, whether as a resident or in the role of teacher. There is no question that editors and contributing authors have hit their target. The reader is left with a strong understanding of the six core competencies and their application to the learning, teaching, and practicing of anesthesiology. Now about that hand washing, which competency does it fall under?University of Tennessee Graduate School of Medicine, Knoxville, Tennessee. dbustama@utmck.edu

This study aims to develop an e-module based on the CinQASE learning model supported by Flip PDF Professional and evaluate its effectiveness in improving students' Individual Critical Thinking (InCT) and collaborative skills in Momentum and Impulse materials. This study employed an R&D approach based on the 4D development model (Define, Design, Develop, Disseminate), comprising four main stages. In the Define stage, a needs analysis was conducted to identify the essential competencies and materials aligned with the curriculum and students' needs. The Design stage focused on designing the e-module structure, determining learning strategies, and compiling learning components, including worksheets and supporting media. The Develop stage included product development, validation by subject matter and media experts, and revisions based on feedback to ensure content quality and suitability. The Disseminate stage was conducted through limited and extensive trials to assess the practicality, readability, and effectiveness of e-modules in real-world learning contexts. Research instruments included expert validation sheets, student and teacher response questionnaires, collaborative activity observation sheets, and InCT tests to assess individual improvements in critical thinking skills. The results showed that the e-module had very high validity across construct, content, graphics, electronic media, materials, presentation, and language, and was considered practical and easy to use by both students and teachers. N-Gain analysis indicated a significant increase in all InCT indicators, from the moderate category in limited tests (0.40–0.45) to the high category in extensive tests (0.68–0.74). Collaborative activities through CinQASE indicator-based worksheets proved effective in encouraging active participation, critical discussion, and peer evaluation. These findings indicate that CinQASE-based e-modules supported by Flip PDF Professional serve as effective interactive learning media for improving students' critical and collaborative thinking skills, while also providing an engaging, flexible, and accessible learning tool for both teachers and students. Keywords: CinQASE, e-modul, Flip PDF, critical thinking skills, collaborative abilities, momentum, and impulse.

The study presents a scientometric analysis of the development of Malay linguistics research over the past three decades. Due to rapid technological changes in linguistics and policy needs, this study examines publication trends, institution and country contributions, themes, and co-citation cluster networks to provide an overview of the field's intellectual structure. The study utilises CiteSpace version 6.3. R3 Advance to analyse records from the Scopus database (1994-2024). The findings indicate substantial growth in publication output, with Malaysia publishing the most papers, followed by Indonesia, Australia, Singapore, and Brunei Darussalam. Universiti Kebangsaan Malaysia, Universiti Sains Malaysia, Universiti Malaya, Universiti Putra Malaysia, Universiti Teknologi Mara, and International Islamic University of Malaysia are the top contributing institutions to research in Malay linguistics. The emerging themes indicate a shift in research focus from traditional linguistic studies toward computational linguistics, digital text processing, and AI-driven applications. The key research clusters were identified, spanning dialectology, historical linguistics, sociolinguistics, and computational linguistics. Among influential contributors, Asmah Haji Omar, with a citation count of 55 and burstness of 4.08, is the most influential author, significantly shaping the discipline. The GEMA Online Journal of Language Studies has the highest citation bursts (1.81), which are crucial in advancing research in computational linguistics, sociolinguistics, and language identity. This study provides critical insights into the evolution of Malay linguistics research, offering valuable evidence to guide researchers and education policymakers in formulating strategic policies for academic innovation and disciplinary advancement.

Students need critical thinking, creativity, communication and collaboration skills to face and adapt to social change, so that students can survive and compete well in social life. The aim of the research is to describe the critical thinking, collaboration, communication and creativity skills of high school students in biology learning. The research was carried out in August-September 2023. The research population was high school students in Magetan Regency. The research sampling technique was cluster sampling and the research sample was 539 high school class students. Data collection techniques used questionnaires on critical thinking skills, communication, collaboration and creativity. This research instrument is a questionnaire in the form of a questionnaire with 5 Likert scales. Quantitative descriptive research data analysis techniques. The research results show that high school students' critical thinking and creativity skills are in the medium and low categories compared to communication and collaboration skills. The results of the research can be used as a reflection for teachers or future researchers as a follow-up to empower students' critical thinking, communication, collaboration and creativity skills in implementing the Merdeka Curriculum.

BackgroundModern clinical practice increasingly relies on collaborative, cooperative and team-based approaches for effective patient care. Recently, Jigsaw cooperative learning has gained attention in medical education. There is a need for studies in Southeast Asian context to establish its effectives in developing various core competencies expected of health professionals such as interpersonal, communication, collaborative, and teamwork skills. This current study explores the impact of using Jigsaw Cooperative Learning on undergraduate medical students.MethodAn explanatory mixed method research design was carried out on first year medical students at a private university in Malaysia. In Phase I, a survey was conducted to explore the effectiveness of jigsaw learning. Descriptive and inferential statistics were calculated using SPSS. In Phase II, a focus group interview was conducted to explore their in-depth experiences. Qualitative data were thematically analysed.ResultsFifty-seven students participated in the survey and seven students took part in the focus group interview. Quantitative data analysis showed a statistically significant improvement in the student’s individual accountability, promotive interaction, positive interdependence, interpersonal skill, communication skill, teamwork skill, critical thinking and consensus building after jigsaw learning sessions. Qualitative data explained their experiences in-depth.ConclusionJigsaw cooperative learning improves collaboration, communication, cooperation and critical thinking among the undergraduate medical students. Educators should use jigsaw learning methods to encourage effective collaboration and team working. Future studies should explore the effectiveness of the jigsaw cooperative learning technique in promoting interprofessional collaboration in the workplace.

Shlomo Argamon is Professor of Computer Science and Director of the Master of Data Science Program at the Illinois Institute of Technology (USA). In this article, he reflects on the current and potential relationship between register and the field of computational linguistics. He applies his expertise in computational linguistics and machine learning to a variety of problems in natural language processing. These include stylistic variation, forensic linguistics, authorship attribution, and biomedical informatics. He is particularly interested in the linguistic structures used by speakers and writers, including linguistic choices that are influenced by social variables such as age, gender, and register, as well as linguistic choices that are unique or distinctive to the style of individual authors. Argamon has been a pioneer in computational linguistics and NLP research in his efforts to account for and explore register variation. His computational linguistic research on register draws inspiration from Systemic Functional Linguistics, Biber’s multi-dimensional approach to register variation, as well as his own extensive experience accounting for variation within and across text types and authors. Argamon has applied computational methods to text classification and description across registers – including blogs, academic disciplines, and news writing – as well as the interaction between register and other social variables, such as age and gender. His cutting-edge research in these areas is certain to have a lasting impact on the future of computational linguistics and NLP.

William C. Mann passed away on August 13, 2004, after a long struggle with leukemia. He is known to readers of Computational Linguistics as a keen supporter and past president (1987) of ACL, a pioneer in the development of text generation as a field of research in computational linguistics, the originator of rhetorical structure theory (RST) and dialogue game theory (DGT), and the developer (together with David Weber) of dialect adaptation as a technique within machine translation. And he’ll be remembered for these and many other contributions, but above all, in this context, he’ll be remembered as a unique visionary in computational linguistics (CL) and as a truly wonderful and extraordinarily generous colleague. Bill Mann made huge contributions to many people’s intellectual development, to their careers, and to their lives in general. What follows are my own recollections of him, selected from a crowded jungle of memories. I will leave it to others to fill out the picture, but I shall attempt to give an indication of the intellectual and historical context in which Bill was working and also of the network of researchers that he created; his ideas have radiated throughout this network of scholars around the world. I met Bill in April 1980 and worked as a research linguist on a succession of projects he directed, or codirected, at the Information Sciences Institute (ISI) at the University of Southern California (USC), until I left the institute to take up a position at the University of Sydney in August 1988. Through that period (which happened to coincide, more or less, with the Reagan years), not only was Bill a very wise and wonderful project leader, but he also became a mentor and guide and a true friend. I followed from afar the further developments in his life: his departure from ISI and move to Kenya with his family to take up a position with the Summer Institute of Linguistics (SIL) as a consultant responsible for work on discourse and computational matters, their return to the United States, and his new phase of research with initiatives in RST and DGT.

Introduction. Donald Walker: a Remembrance. Section 1: The Task of Natural Language Processing. Natural Language Processing: an Historical Review K. Sparck Jones. On Getting a Computer to Listen J. Robinson. Utterance and Objective: Issues in Natural Language Communication B. Grosz. On the Proper Place of Semantics in Machine Translation M. King. Developing a Natural Language Interface to Complex Data G.G. Hendrix, E.D. Sacerdoti. User-Needs Analysis and Design Methodology for an Automated Document Generator K. Kukich, K. McKeown, J. Shaw, J. Robin, J. Lim, N. Morgan, J. Philips. Section 2: Building Computational Lexicons. Machine-Readable Dictionaries and Computational Linguistics Research B. Boguraev. Research Toward the Development of a Lexical Knowledge Base for Natural Language Processing R.A. Amsler. Discovering Relationships Among Word Senses R.J. Byrd. Machine Readable Dictionary as a Source of Grammatical Information E. Hajicova, A. Rosen. The ITT Lexical Database: Dream and Reality S. Pin-Ngern Conlon. Visions of the Digital Library: Views on Using Computational Linguistics and Semantic Nets in Information Retrieval J.L. Klavans. Anatomy of a Verb Entry: from Linguistic Theory to Lexicographic Practice B.T. Atkins, J. Kegl, B. Levin. Issues for Lexicon Building N. Calzolari. Outline of a Model for Lexical Databases N. Ide, J. le Maitre, J. Veronts. Construction-Based MT Lexicons L. Levin, S. Nirenburg. Dependency-Based Grammatical Information in the Lexicon P. Sgall. Semantics in the Brain's Lexicon -- Some Preliminary Remarks on its Epistemology H. Schnelle. Section 3: The Acquisition and Use of LargeCorpora. The Ecology of Language D.E. Walker. Representativeness in Corpus Design D. Biber. The Text Encoding Initiative C.M. Sperberg-McQueen. Discrimination Decisions for 100,000 Dimensional W.A. Gale, K.W. Church, D. Yarowsky. Acquisition and Exploitation of Textual Resources for NLP S. Armstrong-Warwick. The Center for Electronic Texts in the Humanities S. Hockey. Design Principles for Electronic Textual Resources: Investigating Users and Uses of Scholarly Information N.J. Belkin. Section 4: Topics, Methods and Formalisms in Syntax, Semantics and Pragmatics. Evaluating English Sentences in a Logical Model J. Friedman, D.B. Moran, D.S. Warren. Recovering Implicit Information M.S. Palmer, D.A. Dahl, R.J. Schiffman, L. Hirschman, M. Linebarger, J. Downing. Flexible Generation: Taking the User into Account C.L. Paris, V.O. Mittal. Two Principles of Parse Preference J.R. Hobbs, J. Bear. UD, yet Another Unification Device R. Johnson, M. Rosner. Varieties of Heuristics in Sentence Parsing M. Nagao. Some Recent Trends in Natural Language Processing A.K. Joshi. Stone Soup and the French Room Y. Wilks.

Flipped Classroom is a learning model that reverses the habits of traditional learning methods, usually learning activities carried out in class such as understanding the material, then done at home, while assignments or homework that is usually done at home is done in class. This approach encourages students to be more independent and responsible for their own learning process, with the teacher acting as a facilitator. Since its implementation by Bergmann and Sams in 2007, the flipped classroom has become an increasingly popular pedagogical strategy. In the context of curriculum development and educational transformation in the digital era, the flipped classroom can be integrated into the current student-based system. (student-centered learning), collaboration and digital literacy, especially in English language teaching. Integrating a flipped classroom approach using digital media can support curriculum objectives by offering flexibility, effectiveness and innovation in learning. This approach makes it easier for students to learn and understand materials through digital media at home, and focus on active discussion and practice in class. Curriculum in the digital era adapts to prepare students to have critical, collaborative and creative thinking skills. With information and communication technology, utilizing digital media such as learning videos, interactive modules, and online discussion platforms into the flipped classroom approach will allow students to access materials and information more flexibly and in-depth.

The progressiveness of the quality of education in formal educational institutions is implemented through a number of strategies, namely strengthening the readiness of new students, improving teacher competence, updating the curriculum, improving the quality of learning and evaluation of learning outcomes, providing adequate teaching materials, and providing adequate learning facilities. The data analysis techniques implemented involve quantitative and qualitative approaches. Quantitative analysis was carried out by comparing the results of the pretest and posttest using descriptive statistics to measure the progressiveness of the population of competencies of 13 teachers of SMPN 3 Numfor Barat and 13 teachers of SMKN 3 Kemaritiman Biak after training. Partner teachers in Numfor Papua face a number of significant challenges in improving the quality of learning. One of the main problems is the low understanding of the innovative deep learning approach, focusing on comprehensive student involvement in the learning process in order to develop critical, creative, and collaborative thinking skills. research findings indicate that a number of 20 teachers at SMPN 3 and SMKN Kemaritiman Numfor Papua experienced progressive abilities in designing and implementing deep learning strategies that focus on critical, creative, and joyful learning thinking and the implementation of deep learning, especially joyful learning, teachers are able to create a dynamic and meaningful learning atmosphere for students.

We propose the concept of Contested Collective Intelligence (CCI) as a distinctive subset of the broader Collective Intelligence design space. CCI is relevant to the many organizational contexts in which it is important to work with contested knowledge, for instance, due to different intellectual traditions, competing organizational objectives, information overload or ambiguous environmental signals. The CCI challenge is to design sociotechnical infrastructures to augment such organizational capability. Since documents are often the starting points for contested discourse, and discourse markers provide a powerful cue to the presence of claims, contrasting ideas and argumentation, discourse and rhetoric provide an annotation focus in our approach to CCI. Research in sensemaking, computer-supported discourse and rhetorical text analysis motivate a conceptual framework for the combined human and machine annotation of texts with this specific focus. This conception is explored through two tools: a social-semantic web application for human annotation and knowledge mapping (Cohere), plus the discourse analysis component in a textual analysis software tool (Xerox Incremental Parser: XIP). As a step towards an integrated platform, we report a case study in which a document corpus underwent independent human and machine analysis, providing quantitative and qualitative insight into their respective contributions. A promising finding is that significant contributions were signalled by authors via explicit rhetorical moves, which both human analysts and XIP could readily identify. Since working with contested knowledge is at the heart of CCI, the evidence that automatic detection of contrasting ideas in texts is possible through rhetorical discourse analysis is progress towards the effective use of automatic discourse analysis in the CCI framework.

In 21st-century learning, students are required to develop critical thinking and collaboration skills. Project-Based Learning (PjBL) integrated with gamification is considered a potential approach to support these competencies. This study aimed to examine the effect of gamification-assisted PjBL on Grade X students’ critical thinking and collaboration skills in the biodiversity topic at SMAN 21 Medan. The study employed a quasi-experimental method using a Non-Equivalent Control Group design, involving class X5 as the experimental group and class X7 as the control group selected through random sampling. Critical thinking skills were measured using ten essay questions representing five indicators, while collaboration skills were assessed through an observation sheet based on four indicators. The results showed a significant difference between the experimental and control groups. The t-test analysis of critical thinking skills yielded a significance value of 0.016 (< 0.05), with the experimental group achieving a higher posttest mean score (75.25) than the control group (61.60). Similarly, collaboration skills showed a significant difference with a significance value of < 0.001. These findings indicate that gamification-assisted PjBL has a positive effect on improving students’ critical thinking and collaboration skills compared to PjBL without gamification. Therefore, it is recommended that biology teachers integrate gamification elements such as points, badges, and challenges into project-based learning to enhance students’ critical thinking and collaboration skills.

Background: The rapid development of 21st-century education requires a paradigm shift from teacher-centered learning toward learner-centered approaches that emphasize deep learning. In the context of non-formal education, Community Learning Centers (Pusat Kegiatan Belajar Masyarakat, PKBM) serve as strategic spaces for lifelong learning. However, many still rely on conventional, one-way instructional practices that limit reflective dialogue and learner engagement. Deep learning, which focuses on critical thinking, collaboration, and knowledge transfer to real-life contexts, has the potential to transform these interactions into more dialogic and meaningful communication processes. Research Objectives: This study aims to analyze the influence of the deep learning model on enhancing dialogic communication during the learning process at community learning center. Additionally, it seeks to examine the extent to which deep learning contributes to the achievement of UNESCO’s four pillars of learning—learning to know, learning to do, learning to be, and learning to live together. Research Method: This research employed a mixed-methods design with an explanatory sequential approach. The quantitative phase used a quasi-experimental method involving 120 learners across six community learning center in Jakarta, divided into experimental and control groups. The experimental group implemented a deep learning model emphasizing reflective questioning and collaborative dialogue, while the control group applied conventional methods. Quantitative data were analyzed using t-tests and multiple linear regression, while qualitative data were gathered through interviews and observations, then analyzed thematically to provide contextual understanding. Research Findings: The results showed that learners in the experimental group experienced a significant improvement in dialogic communication compared to the control group (t = 6.42; p = 0.000). Their mean score increased from 61.2 to 84.3, demonstrating enhanced participation, reflection, and critical dialogue. Multiple regression analysis revealed that deep learning was a dominant predictor of achieving the four pillars of learning (β = 0.68; p = 0.000), explaining 53% of the variance in holistic learning outcomes. Qualitative findings supported these results, illustrating that learners perceived the deep learning environment as challenging yet meaningful, fostering curiosity, collaboration, and a sense of empowerment. Conclusion: The study concludes that deep learning significantly strengthens dialogic communication and holistic learning in non-formal education contexts. By integrating reflection, collaboration, and authentic problem-solving, this approach transforms community learning center classrooms into inclusive and participatory learning spaces. It not only enhances cognitive and social skills but also aligns with the broader mission of community empowerment through lifelong learning. Novelty/Originality/Value: This study provides one of the first empirical investigations linking deep learning with dialogic communication in Indonesian non-formal education settings. It offers a practical model for community learning center tutors to foster transformative learning interactions and contributes to policy discussions on enhancing pedagogical capacity in community-based education.

Critical thinking and social reasoning are fundamental skills in complex, social situations, and several domains (e.g., healthcare and military) have realized that personnel are lacking the cognitive skills necessary to optimally perform within their complicated, dynamic environment. Thus, there is a need to train critical social thinking skills in order to improve cognitive and social reasoning, enhance performance, and ultimately result in better outcomes. Therefore the purpose of this paper is to provide researchers and practitioners with a review of the literature pertinent to developing critical social thinking skills. This review is presented in the form of best practices for designing and implementing critical thinking training interventions.