Objective To investigate methods for constructing a high-quality instructional dataset for traditional Chinese medicine(TCM)mental disorders and to validate its efficacy.Methods We proposed the Fine-Med-Mental-T&P...Objective To investigate methods for constructing a high-quality instructional dataset for traditional Chinese medicine(TCM)mental disorders and to validate its efficacy.Methods We proposed the Fine-Med-Mental-T&P methodology for constructing high-quality instruction datasets in TCM mental disorders.This approach integrates theoretical knowledge and practical case studies through a dual-track strategy.(i)Theoretical track:textbooks and guidelines on TCM mental disorders were manually segmented.Initial responses were generated using DeepSeek-V3,followed by refinement by the Qwen3-32B model to align the expression with human preferences.A screening algorithm was then applied to select 16000 high-quality instruction pairs.(ii)Practical track:starting from over 600 real clinical case seeds,diagnostic and therapeutic instruction pairs were generated using DeepSeek-V3 and subsequently screened through manual evaluation,resulting in 4000 high-quality practiceoriented instruction pairs.The integration of both tracks yielded the Med-Mental-Instruct-T&P dataset,comprising a total of 20000 instruction pairs.To validate the dataset’s effectiveness,three experimental evaluations(both manual and automated)were conducted:(i)comparative studies to compare the performance of models fine-tuned on different datasets;(ii)benchmarking to compare against mainstream TCM-specific large language models(LLMs);(iii)data ablation study to investigate the relationship between data volume and model performance.Results Experimental results demonstrate the superior performance of T&P-model finetuned on the Med-Mental-Instruct-T&P dataset.In the comparative study,the T&P-model significantly outperformed the baseline models trained solely on self-generated or purely human-curated baseline data.This superiority was evident in both automated metrics(ROUGEL>0.55)and expert manual evaluations(scoring above 7/10 across accuracy).In benchmark comparisons,the T&P-model also excelled against existing mainstream TCM LLMs(e.g.,HuatuoGPT and ZuoyiGPT).It showed particularly strong capabilities in handling diverse clinical presentations,including challenging disorders such as insomnia and coma,showcasing its robustness and versatility.Data ablation studies showed that T&P-model performance had an overall upward trend with minor fluctuations when training data increased from 10%to 50%;beyond 50%,performance improvement slowed significantly,with metrics plateauing and approaching a saturation point.展开更多
Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal’s official website http://www.keaipublishing.com/dcmed under...Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal’s official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.展开更多
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
The problem of fake news detection(FND)is becoming increasingly important in the field of natural language processing(NLP)because of the rapid dissemination of misleading information on the web.Large language models(L...The problem of fake news detection(FND)is becoming increasingly important in the field of natural language processing(NLP)because of the rapid dissemination of misleading information on the web.Large language models(LLMs)such as GPT-4.Zero excels in natural language understanding tasks but can still struggle to distinguish between fact and fiction,particularly when applied in the wild.However,a key challenge of existing FND methods is that they only consider unimodal data(e.g.,images),while more detailed multimodal data(e.g.,user behaviour,temporal dynamics)is neglected,and the latter is crucial for full-context understanding.To overcome these limitations,we introduce M3-FND(Multimodal Misinformation Mitigation for False News Detection),a novel methodological framework that integrates LLMs with multimodal data sources to perform context-aware veracity assessments.Our method proposes a hybrid system that combines image-text alignment,user credibility profiling,and temporal pattern recognition,which is also strengthened through a natural feedback loop that provides real-time feedback for correcting downstream errors.We use contextual reinforcement learning to schedule prompt updating and update the classifier threshold based on the latest multimodal input,which enables the model to better adapt to changing misinformation attack strategies.M3-FND is tested on three diverse datasets,FakeNewsNet,Twitter15,andWeibo,which contain both text and visual socialmedia content.Experiments showthatM3-FND significantly outperforms conventional and LLMbased baselines in terms of accuracy,F1-score,and AUC on all benchmarks.Our results indicate the importance of employing multimodal cues and adaptive learning for effective and timely detection of fake news.展开更多
Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls fo...Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls for"strengthening the training of nutrition talents"and"promoting nutrition science education".As a key vehicle for this mission,the Food Nutrition and Health course in higher education urgently needs to address bottlenecks in traditional teaching,such as low knowledge application and transfer rates,insufficient student engagement,and ineffective guidance on healthy behaviors.The BOPPPS teaching model,with its structured design(Bridge-in,Objective,Pre-assessment,Participatory Learning,Post-assessment,Summary),effectively promotes the internalization of nutritional knowledge and the transformation into healthy behaviors among students by emphasizing practice-oriented teaching activities.In this study,focusing on this course,an in-depth exploration of curriculum teaching design was conducted based on the BOPPPS instructional model,aiming to deeply integrate the strategic objectives of Healthy China into the curriculum,and promote the transformation of nutritional knowledge into healthy decision-making ability.This study provides new insights for food and nutrition education.展开更多
Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
CLIL,which stands for Content and Language Integrated Learning,is an instructional approach that gives ample curricular and pedagogical attention to content and language outcomes in multilingual educational settings.I...CLIL,which stands for Content and Language Integrated Learning,is an instructional approach that gives ample curricular and pedagogical attention to content and language outcomes in multilingual educational settings.Increasingly,it is heralded as a way to responsibly enact top-down English-Medium-of-Instruction(EMI)policies at the university level,where teachers and students are tasked with developing their English proficiency while remaining competitive in the international job market.However,teachers and teacher educators hoping to implement this approach in their science,technology,engineering and mathematics(STEM)content courses face significant challenges.This article serves as an introduction to a vip-edited special issue that reports on several aspects related to a project of international collaboration called Project SCILLA,an acronym for“STEM Content Integrated with Language-Learning Activities”.We first provide a brief overview of the project,which was developed and carried out in collaboration between Michigan State University and a consortium of 10 rural universities in Kazakhstan as a way to support STEM educators who wish to adapt their teaching practices to Kazakhstan’s Ministry of Education.We then offer an overview of the six articles that comprise the special issue,and call for deliberate and dialogic international collaboration as a way to support teachers responding to language policy demands.展开更多
In L2 content-based classrooms,code-switching or translanguaging seem to be a common practice adopted by teachers.There has been growing research discussing the potentials of L1 in these classrooms.Most of the current...In L2 content-based classrooms,code-switching or translanguaging seem to be a common practice adopted by teachers.There has been growing research discussing the potentials of L1 in these classrooms.Most of the current studies have focused on the analysis of lesson interactions and yet the perception of the content teachers has remained underexplored.This case study investigated the introspective views of a group of content teachers at a secondary school using questionnaires and written accounts.Data analyses showed that these teachers were generally aware of the interpersonal and ideational functions achieved by the use of L1 and they also seemed to have a positive view towards their practices of using L1 in English-medium classrooms.Based on the findings,practical implications for content teachers in relation to making medium of instruction decisions and suggestions for further research are discussed.展开更多
Find It What did the old woman give Lucy?Once upon a time,a poor girl named Lucy lived in a small village.She was kind and helped others when she could.But she and her mother were often very hungry because they were p...Find It What did the old woman give Lucy?Once upon a time,a poor girl named Lucy lived in a small village.She was kind and helped others when she could.But she and her mother were often very hungry because they were poor.展开更多
The adoption of content and language integrated learning(CLIL)practices has expanded in recent years as higher education institutions adopt a top-down English medium of instruction(EMI)language policy in the hope of e...The adoption of content and language integrated learning(CLIL)practices has expanded in recent years as higher education institutions adopt a top-down English medium of instruction(EMI)language policy in the hope of entering the international knowledge market(De Costa et al.,2022;Isidro&Lasagabaster,2019).However,research focusing on the effects of EMI policy on content teachers needing to implement CLIL,especially within trilingual contexts such as Kazakhstan,has been marginal despite drastic alterations to teachers’professional context and expectations(Karabassova,2022b).Such changes may result in teachers’feelings of professional vulnerability-an emotion that often arises when changes in professional expectations and professional context disrupt one’s professional identity and pedagogical practices(Kelchtermans,2009).Our case study focuses on the professional vulnerability experienced by a Kazakhstani in-service teacher as she negotiated a CLIL pedagogy for the first time.Relying on semi-structured interviews,recorded classroom observation,field notes,and developed material,our findings highlight how macro(e.g.,societal)and meso(e.g.,institutional)language policies can affect teachers’lived experiences and pedagogical practices within their classrooms.Lastly,we provide ways in which administrators can assist teachers in overcoming professional vulnerability as institutions adopt language policies such as CLIL.展开更多
Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal's official website http://www.keaipublishing.com/dcmed un...Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal's official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.展开更多
Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal’s official website http://www.keaipublishing.com/dcmed under...Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal’s official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.展开更多
Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal's official website http://www.keaipublishing.com/dcmed un...Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal's official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.展开更多
Modules enable students to engage with content at their own pace,fostering autonomy and deeper understanding.The modular approach ensures clarity in presenting objectives,instructions,and concepts,while having illustr...Modules enable students to engage with content at their own pace,fostering autonomy and deeper understanding.The modular approach ensures clarity in presenting objectives,instructions,and concepts,while having illustrations,activities,and assessments could enhance comprehension and retention.This paper was a developmental study on STS module for college students using the ADDIE Model(Analysis,Design,Development,Implementation,and Evaluation).Sampled 673 first-year students from Northwest Samar State University participated in the study,with 299 participating in a test try-out and 374 in the students’performance evaluation.Three expert evaluators with backgrounds in science,English,and psychology,each with over four years of experience,assessed the modules to ensure alignment with the study’s constructivist learning goals and instructional integrity.The findings revealed that both students and experts had rated the instructional module positively,indicating its effectiveness in facilitating learning and completing lessons.Key aspects such as the style of illustrations and written expressions,the usefulness of learning activities,and the guidance provided by illustrations and captions were especially well-received.The module was praised for its clear objectives,understandable instructions,and engaging tasks like trivia and puzzles.Expert evaluations highlighted relevance,simplicity,and balanced emphasis on topics in the module content.Furthermore,students in test group demonstrated significant improvement in performance,with post-test scores notably higher than pre-test scores,confirming the module’s effectiveness in enhancing learning outcomes.Consequently,this paper provides an opportunity to integrate science learning with initiatives aimed at promoting environmental preservation and driving social change.展开更多
This study explores differentiated instructional strategies in higher education,focusing on municipal universities in Beijing to address the needs of students requiring special academic and psychological support.Despi...This study explores differentiated instructional strategies in higher education,focusing on municipal universities in Beijing to address the needs of students requiring special academic and psychological support.Despite standardized cultivation frameworks in universities,significant variations persist among undergraduates in academic planning,cognitive traits,and psychological profiles.A minority of students face challenges due to cognitive misjudgments(e.g.,unrealistic self-assessment),goal fixation(e.g.,excessive focus on postgraduate exams or studying abroad),psychological barriers(e.g.,social withdrawal),or mental health crises,which hinder their academic integration and personal development.Universities must adopt flexible,compliance-oriented differentiated instruction within standardized frameworks to support at-risk students.Strategies should balance personalized interventions with institutional fairness,ensuring equitable opportunities for all students while safeguarding academic integrity.展开更多
Among the four basic skills in language learning,listening seems to present more difficulties for the students in their college English study.This paper tries to examine various obstacles affecting college students’E...Among the four basic skills in language learning,listening seems to present more difficulties for the students in their college English study.This paper tries to examine various obstacles affecting college students’English listening comprehension based on the author’s 20 years of teaching experience.Through systematic analysis of both linguistic and non-linguistic factors,the study proposes targeted teaching methodologies to enhance students’listening proficiency.The research highlights the importance of integrated skill development,psychological factors in language acquisition,and effective listening strategies.Practical classroom techniques are suggested,including the combination of listening and speaking practice,motivation enhancement approaches,and systematic training in listening strategies.The findings emphasize the need for comprehensive solutions addressing multiple dimensions of listening comprehension difficulties in Chinese EFL learners.展开更多
In recent years,artificial intelligence(AI)has been increasingly integrated into educational settings worldwide.This study aims to explore the effectiveness of AI classroom teaching for Chinese undergraduate students,...In recent years,artificial intelligence(AI)has been increasingly integrated into educational settings worldwide.This study aims to explore the effectiveness of AI classroom teaching for Chinese undergraduate students,focusing on its influence on learning outcomes and student engagement.The research uses a quantitative approach,utilizing surveys and academic performance data to evaluate two main objectives:(1)the impact of AI teaching methods on academic performance compared to traditional instruction;(2)the level of student engagement and satisfaction with AI-based learning tools.The study sample includes undergraduate students from multiple universities in China,allowing for a diverse representation of various disciplines.Data will be collected through standardized tests,questionnaires,and academic records,ensuring the reliability and validity of the results.The findings will provide insights into the potential advantages and challenges of AI integration in higher education and inform future strategies for adopting AI in Chinese classrooms.By exploring both the academic and practical aspects of AI-driven education,this research aims to contribute valuable knowledge to the growing field of AI in education,particularly in the context of Chinese higher education.The results are expected to have implications for educators,policymakers,and AI developers interested in enhancing the effectiveness of educational technologies.展开更多
Anesthetic pharmacology,a specialized branch of pharmacology,differs significantly from the foundational pharmacology taught in undergraduate medical programs.A key challenge lies in effectively distinguishing and int...Anesthetic pharmacology,a specialized branch of pharmacology,differs significantly from the foundational pharmacology taught in undergraduate medical programs.A key challenge lies in effectively distinguishing and integrating these two courses to enhance students’theoretical understanding and foster their clinical anesthesia skills.This paper explores strategies for optimizing lesson preparation and delivery in anesthetic pharmacology,focusing on course positioning,student knowledge assessment,clinical integration,objective setting,content development,instructional design,innovative teaching tools,and classroom management.The ultimate aim is to enhance teaching effectiveness and train anesthesiology professionals with robust theoretical knowledge and practical competence.展开更多
基金Key Scientific Research Project of the Hunan Provincial Department of Education(23A312).
文摘Objective To investigate methods for constructing a high-quality instructional dataset for traditional Chinese medicine(TCM)mental disorders and to validate its efficacy.Methods We proposed the Fine-Med-Mental-T&P methodology for constructing high-quality instruction datasets in TCM mental disorders.This approach integrates theoretical knowledge and practical case studies through a dual-track strategy.(i)Theoretical track:textbooks and guidelines on TCM mental disorders were manually segmented.Initial responses were generated using DeepSeek-V3,followed by refinement by the Qwen3-32B model to align the expression with human preferences.A screening algorithm was then applied to select 16000 high-quality instruction pairs.(ii)Practical track:starting from over 600 real clinical case seeds,diagnostic and therapeutic instruction pairs were generated using DeepSeek-V3 and subsequently screened through manual evaluation,resulting in 4000 high-quality practiceoriented instruction pairs.The integration of both tracks yielded the Med-Mental-Instruct-T&P dataset,comprising a total of 20000 instruction pairs.To validate the dataset’s effectiveness,three experimental evaluations(both manual and automated)were conducted:(i)comparative studies to compare the performance of models fine-tuned on different datasets;(ii)benchmarking to compare against mainstream TCM-specific large language models(LLMs);(iii)data ablation study to investigate the relationship between data volume and model performance.Results Experimental results demonstrate the superior performance of T&P-model finetuned on the Med-Mental-Instruct-T&P dataset.In the comparative study,the T&P-model significantly outperformed the baseline models trained solely on self-generated or purely human-curated baseline data.This superiority was evident in both automated metrics(ROUGEL>0.55)and expert manual evaluations(scoring above 7/10 across accuracy).In benchmark comparisons,the T&P-model also excelled against existing mainstream TCM LLMs(e.g.,HuatuoGPT and ZuoyiGPT).It showed particularly strong capabilities in handling diverse clinical presentations,including challenging disorders such as insomnia and coma,showcasing its robustness and versatility.Data ablation studies showed that T&P-model performance had an overall upward trend with minor fluctuations when training data increased from 10%to 50%;beyond 50%,performance improvement slowed significantly,with metrics plateauing and approaching a saturation point.
文摘Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal’s official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.
基金supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
文摘The problem of fake news detection(FND)is becoming increasingly important in the field of natural language processing(NLP)because of the rapid dissemination of misleading information on the web.Large language models(LLMs)such as GPT-4.Zero excels in natural language understanding tasks but can still struggle to distinguish between fact and fiction,particularly when applied in the wild.However,a key challenge of existing FND methods is that they only consider unimodal data(e.g.,images),while more detailed multimodal data(e.g.,user behaviour,temporal dynamics)is neglected,and the latter is crucial for full-context understanding.To overcome these limitations,we introduce M3-FND(Multimodal Misinformation Mitigation for False News Detection),a novel methodological framework that integrates LLMs with multimodal data sources to perform context-aware veracity assessments.Our method proposes a hybrid system that combines image-text alignment,user credibility profiling,and temporal pattern recognition,which is also strengthened through a natural feedback loop that provides real-time feedback for correcting downstream errors.We use contextual reinforcement learning to schedule prompt updating and update the classifier threshold based on the latest multimodal input,which enables the model to better adapt to changing misinformation attack strategies.M3-FND is tested on three diverse datasets,FakeNewsNet,Twitter15,andWeibo,which contain both text and visual socialmedia content.Experiments showthatM3-FND significantly outperforms conventional and LLMbased baselines in terms of accuracy,F1-score,and AUC on all benchmarks.Our results indicate the importance of employing multimodal cues and adaptive learning for effective and timely detection of fake news.
文摘Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls for"strengthening the training of nutrition talents"and"promoting nutrition science education".As a key vehicle for this mission,the Food Nutrition and Health course in higher education urgently needs to address bottlenecks in traditional teaching,such as low knowledge application and transfer rates,insufficient student engagement,and ineffective guidance on healthy behaviors.The BOPPPS teaching model,with its structured design(Bridge-in,Objective,Pre-assessment,Participatory Learning,Post-assessment,Summary),effectively promotes the internalization of nutritional knowledge and the transformation into healthy behaviors among students by emphasizing practice-oriented teaching activities.In this study,focusing on this course,an in-depth exploration of curriculum teaching design was conducted based on the BOPPPS instructional model,aiming to deeply integrate the strategic objectives of Healthy China into the curriculum,and promote the transformation of nutritional knowledge into healthy decision-making ability.This study provides new insights for food and nutrition education.
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
基金funding from the U.S.-Kazakhstan University Partnerships program funded by the U.S.Mission to Kazakhstan and administered by American Councils[Award number SKZ100-19-CA-0149].
文摘CLIL,which stands for Content and Language Integrated Learning,is an instructional approach that gives ample curricular and pedagogical attention to content and language outcomes in multilingual educational settings.Increasingly,it is heralded as a way to responsibly enact top-down English-Medium-of-Instruction(EMI)policies at the university level,where teachers and students are tasked with developing their English proficiency while remaining competitive in the international job market.However,teachers and teacher educators hoping to implement this approach in their science,technology,engineering and mathematics(STEM)content courses face significant challenges.This article serves as an introduction to a vip-edited special issue that reports on several aspects related to a project of international collaboration called Project SCILLA,an acronym for“STEM Content Integrated with Language-Learning Activities”.We first provide a brief overview of the project,which was developed and carried out in collaboration between Michigan State University and a consortium of 10 rural universities in Kazakhstan as a way to support STEM educators who wish to adapt their teaching practices to Kazakhstan’s Ministry of Education.We then offer an overview of the six articles that comprise the special issue,and call for deliberate and dialogic international collaboration as a way to support teachers responding to language policy demands.
文摘In L2 content-based classrooms,code-switching or translanguaging seem to be a common practice adopted by teachers.There has been growing research discussing the potentials of L1 in these classrooms.Most of the current studies have focused on the analysis of lesson interactions and yet the perception of the content teachers has remained underexplored.This case study investigated the introspective views of a group of content teachers at a secondary school using questionnaires and written accounts.Data analyses showed that these teachers were generally aware of the interpersonal and ideational functions achieved by the use of L1 and they also seemed to have a positive view towards their practices of using L1 in English-medium classrooms.Based on the findings,practical implications for content teachers in relation to making medium of instruction decisions and suggestions for further research are discussed.
文摘Find It What did the old woman give Lucy?Once upon a time,a poor girl named Lucy lived in a small village.She was kind and helped others when she could.But she and her mother were often very hungry because they were poor.
基金funding from the U.S.-Kazakhstan University Partnerships program funded by the U.S.Mission to Kazakhstan and administered by American Councils[Award number SKZ100-19-CA-0149].
文摘The adoption of content and language integrated learning(CLIL)practices has expanded in recent years as higher education institutions adopt a top-down English medium of instruction(EMI)language policy in the hope of entering the international knowledge market(De Costa et al.,2022;Isidro&Lasagabaster,2019).However,research focusing on the effects of EMI policy on content teachers needing to implement CLIL,especially within trilingual contexts such as Kazakhstan,has been marginal despite drastic alterations to teachers’professional context and expectations(Karabassova,2022b).Such changes may result in teachers’feelings of professional vulnerability-an emotion that often arises when changes in professional expectations and professional context disrupt one’s professional identity and pedagogical practices(Kelchtermans,2009).Our case study focuses on the professional vulnerability experienced by a Kazakhstani in-service teacher as she negotiated a CLIL pedagogy for the first time.Relying on semi-structured interviews,recorded classroom observation,field notes,and developed material,our findings highlight how macro(e.g.,societal)and meso(e.g.,institutional)language policies can affect teachers’lived experiences and pedagogical practices within their classrooms.Lastly,we provide ways in which administrators can assist teachers in overcoming professional vulnerability as institutions adopt language policies such as CLIL.
文摘Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal's official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.
文摘Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal’s official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.
文摘Submission Before submitting the manuscript,authors should carefully read the“Instructions for Authors”“Submission Walkthrough”available at the journal's official website http://www.keaipublishing.com/dcmed under the“Submission”menu.The manuscript should be accompanied by a cover letter from the author who will be responsible for correspondence.Peer-review and refereeing are made online and anonymously.
文摘Modules enable students to engage with content at their own pace,fostering autonomy and deeper understanding.The modular approach ensures clarity in presenting objectives,instructions,and concepts,while having illustrations,activities,and assessments could enhance comprehension and retention.This paper was a developmental study on STS module for college students using the ADDIE Model(Analysis,Design,Development,Implementation,and Evaluation).Sampled 673 first-year students from Northwest Samar State University participated in the study,with 299 participating in a test try-out and 374 in the students’performance evaluation.Three expert evaluators with backgrounds in science,English,and psychology,each with over four years of experience,assessed the modules to ensure alignment with the study’s constructivist learning goals and instructional integrity.The findings revealed that both students and experts had rated the instructional module positively,indicating its effectiveness in facilitating learning and completing lessons.Key aspects such as the style of illustrations and written expressions,the usefulness of learning activities,and the guidance provided by illustrations and captions were especially well-received.The module was praised for its clear objectives,understandable instructions,and engaging tasks like trivia and puzzles.Expert evaluations highlighted relevance,simplicity,and balanced emphasis on topics in the module content.Furthermore,students in test group demonstrated significant improvement in performance,with post-test scores notably higher than pre-test scores,confirming the module’s effectiveness in enhancing learning outcomes.Consequently,this paper provides an opportunity to integrate science learning with initiatives aimed at promoting environmental preservation and driving social change.
文摘This study explores differentiated instructional strategies in higher education,focusing on municipal universities in Beijing to address the needs of students requiring special academic and psychological support.Despite standardized cultivation frameworks in universities,significant variations persist among undergraduates in academic planning,cognitive traits,and psychological profiles.A minority of students face challenges due to cognitive misjudgments(e.g.,unrealistic self-assessment),goal fixation(e.g.,excessive focus on postgraduate exams or studying abroad),psychological barriers(e.g.,social withdrawal),or mental health crises,which hinder their academic integration and personal development.Universities must adopt flexible,compliance-oriented differentiated instruction within standardized frameworks to support at-risk students.Strategies should balance personalized interventions with institutional fairness,ensuring equitable opportunities for all students while safeguarding academic integrity.
文摘Among the four basic skills in language learning,listening seems to present more difficulties for the students in their college English study.This paper tries to examine various obstacles affecting college students’English listening comprehension based on the author’s 20 years of teaching experience.Through systematic analysis of both linguistic and non-linguistic factors,the study proposes targeted teaching methodologies to enhance students’listening proficiency.The research highlights the importance of integrated skill development,psychological factors in language acquisition,and effective listening strategies.Practical classroom techniques are suggested,including the combination of listening and speaking practice,motivation enhancement approaches,and systematic training in listening strategies.The findings emphasize the need for comprehensive solutions addressing multiple dimensions of listening comprehension difficulties in Chinese EFL learners.
文摘In recent years,artificial intelligence(AI)has been increasingly integrated into educational settings worldwide.This study aims to explore the effectiveness of AI classroom teaching for Chinese undergraduate students,focusing on its influence on learning outcomes and student engagement.The research uses a quantitative approach,utilizing surveys and academic performance data to evaluate two main objectives:(1)the impact of AI teaching methods on academic performance compared to traditional instruction;(2)the level of student engagement and satisfaction with AI-based learning tools.The study sample includes undergraduate students from multiple universities in China,allowing for a diverse representation of various disciplines.Data will be collected through standardized tests,questionnaires,and academic records,ensuring the reliability and validity of the results.The findings will provide insights into the potential advantages and challenges of AI integration in higher education and inform future strategies for adopting AI in Chinese classrooms.By exploring both the academic and practical aspects of AI-driven education,this research aims to contribute valuable knowledge to the growing field of AI in education,particularly in the context of Chinese higher education.The results are expected to have implications for educators,policymakers,and AI developers interested in enhancing the effectiveness of educational technologies.
基金supported by Collaborative Education Project of the Ministry of Education of China(250101414020206)Planning Project of Shanghai Higher Education Association(2QYB24158).
文摘Anesthetic pharmacology,a specialized branch of pharmacology,differs significantly from the foundational pharmacology taught in undergraduate medical programs.A key challenge lies in effectively distinguishing and integrating these two courses to enhance students’theoretical understanding and foster their clinical anesthesia skills.This paper explores strategies for optimizing lesson preparation and delivery in anesthetic pharmacology,focusing on course positioning,student knowledge assessment,clinical integration,objective setting,content development,instructional design,innovative teaching tools,and classroom management.The ultimate aim is to enhance teaching effectiveness and train anesthesiology professionals with robust theoretical knowledge and practical competence.
