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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
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In: Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021) ; https://hal.archives-ouvertes.fr/hal-03466171 ; Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), Aug 2021, Online, France. pp.96-120, ⟨10.18653/v1/2021.gem-1.10⟩ (2021)
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BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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Pre-train or Annotate? Domain Adaptation with a Constrained Budget ...
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BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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Sample data for "Design and Collection Challenges of Building an Academic Email Corpus for Linguistics and Computational Research" ...
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Sample data for "Design and Collection Challenges of Building an Academic Email Corpus for Linguistics and Computational Research" ...
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Controllable Text Simplification with Explicit Paraphrasing ...
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The effectiveness of the problem-based learning in medical cell biology education: A systematic meta-analysis
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In: Medicine (Baltimore) (2021)
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Abstract:
BACKGROUND: Problem-based learning (PBL) was widely adopted in medical cell biology education for Chinese student; however, there was no systematic analysis to prove PBL was much more effective than lecture-based learning (LBL). Our aim is to evaluate the effectiveness of PBL on cell biology curriculum compared with LBL. METHOD: We systematically searched the publications related to PBL teaching approach in cell biology curriculum for medical education from databases until to February 2021. Pooled standard mean differences (SMDs) and risk ratios with their 95% confidence intervals were used to assess the effectiveness of PBL and the satisfaction of students to PBL compared to LBL in meta-analysis. The heterogeneity of the included studies was assessed by statistical I(2) of heterogeneity. Meta-regression and subgroup analysis were performed to analyze the source of heterogeneity. Funnel plots and Egger tests were performed to assess publication bias. RESULT: After initial searching and selection, 9 studies were included for meta-analysis. All of these 9 studies were in high quality. The SMDs (95% confidence intervals) of total examination scores and comprehensive examination scores between PBL and LBL curriculum in cell biology teaching was calculated to be 0.89 (0.52, 1.26) and 0.53 (0.29, 0.78). Meanwhile, the risk ratios of the satisfaction of PBL vs LBL were calculated to be 1.18 (0.96, 1.46). However, there was a heterogeneity among the pooled SMDs of 10 studies with I(2) = 89.7%, P < .001. The factors including the different teachers, the similar or same examination paper and over 100 student numbers among PBL and LBL groups raised the heterogeneity in the pooled SMDs. There is no publication bias in these 10 publications after Egger and Begg test. CONCLUSION: The result indicated PBL was better than LBL in improvement of examination scores and comprehensive examination scores in cell biology curriculum to some extent. However, the satisfaction of students to PBL and LBL had no difference. The factors, including the different teachers, the similar or same examination papers and over 100 student numbers, affected the effectiveness of PBL and raised the heterogeneity of the pooled SMDs.
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Keyword:
5400
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URL: https://doi.org/10.1097/MD.0000000000027402 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483832/ http://www.ncbi.nlm.nih.gov/pubmed/34596166
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Controllable text simplification with explicit paraphrasing
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An Empirical Study of Pre-trained Transformers for Arabic Information Extraction ...
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Controllable Text Simplification with Explicit Paraphrasing ...
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Interactive Grounded Language Acquisition and Generalization in a 2D World ...
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Interactive Language Acquisition with One-shot Visual Concept Learning through a Conversational Game ...
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Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents ...
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A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification ...
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A Deep Compositional Framework for Human-like Language Acquisition in Virtual Environment ...
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A Continuously Growing Dataset of Sentential Paraphrases ...
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Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task
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