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Academic literature on the topic 'Knowledge Base Completion'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Knowledge Base Completion"

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Choi, Hyun-Young, Ji-Hun Hong, Wan-Gon Lee, Batselem Jagvaral, Myung-Joong Jeon, Hyun-Kyu Park, and Young-Tack Park. "Knowledge Completion Modeling using Knowledge Base Embedding." Journal of KIISE 45, no. 9 (September 30, 2018): 895–903. http://dx.doi.org/10.5626/jok.2018.45.9.895.

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Choi, Su Jeong, Hyun-Je Song, and Seong-Bae Park. "An Approach to Knowledge Base Completion by a Committee-Based Knowledge Graph Embedding." Applied Sciences 10, no. 8 (April 11, 2020): 2651. http://dx.doi.org/10.3390/app10082651.

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Knowledge bases such as Freebase, YAGO, DBPedia, and Nell contain a number of facts with various entities and relations. Since they store many facts, they are regarded as core resources for many natural language processing tasks. Nevertheless, they are not normally complete and have many missing facts. Such missing facts keep them from being used in diverse applications in spite of their usefulness. Therefore, it is significant to complete knowledge bases. Knowledge graph embedding is one of the promising approaches to completing a knowledge base and thus many variants of knowledge graph embedding have been proposed. It maps all entities and relations in knowledge base onto a low dimensional vector space. Then, candidate facts that are plausible in the space are determined as missing facts. However, any single knowledge graph embedding is insufficient to complete a knowledge base. As a solution to this problem, this paper defines knowledge base completion as a ranking task and proposes a committee-based knowledge graph embedding model for improving the performance of knowledge base completion. Since each knowledge graph embedding has its own idiosyncrasy, we make up a committee of various knowledge graph embeddings to reflect various perspectives. After ranking all candidate facts according to their plausibility computed by the committee, the top-k facts are chosen as missing facts. Our experimental results on two data sets show that the proposed model achieves higher performance than any single knowledge graph embedding and shows robust performances regardless of k. These results prove that the proposed model considers various perspectives in measuring the plausibility of candidate facts.
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Srinivasa, K., and P. Santhi Thilagam. "Clustering and Bootstrapping Based Framework for News Knowledge Base Completion." Computing and Informatics 40, no. 2 (2021): 318–40. http://dx.doi.org/10.31577/cai_2021_2_318.

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Lin, Xixun, Yanchun Liang, Limin Wang, Xu Wang, Mary Qu Yang, and Renchu Guan. "A Knowledge Base Completion Model Based on Path Feature Learning." International Journal of Computers Communications & Control 13, no. 1 (February 12, 2018): 71. http://dx.doi.org/10.15837/ijccc.2018.1.3104.

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Large-scale knowledge bases, as the foundations for promoting the development of artificial intelligence, have attracted increasing attention in recent years. These knowledge bases contain billions of facts in triple format; yet, they suffer from sparse relations between entities. Researchers proposed the path ranking algorithm (PRA) to solve this fatal problem. To improve the scalability of knowledge inference, PRA exploits random walks to find Horn clauses with chain structures to predict new relations given existing facts. This method can be regarded as a statistical classification issue for statistical relational learning (SRL). However, large-scale knowledge base completion demands superior accuracy and scalability. In this paper, we propose the path feature learning model (PFLM) to achieve this urgent task. More precisely, we define a two-stage model: the first stage aims to learn path features from the existing knowledge base and extra parsed corpus; the second stage uses these path features to predict new relations. The experimental results demonstrate that the PFLM can learn meaningful features and can achieve significant and consistent improvements compared with previous work.
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Hamaguchi, Takuo, Hidekazu Oiwa, Masashi Shimbo, and Yuji Matsumoto. "Knowledge Base Completion with Out-of-Knowledge-Base Entities: A Graph Neural Network Approach." Transactions of the Japanese Society for Artificial Intelligence 33, no. 2 (2018): F—H72_1–10. http://dx.doi.org/10.1527/tjsai.f-h72.

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Kong, Fanshuang, Richong Zhang, Yongyi Mao, and Ting Deng. "LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 2895–902. http://dx.doi.org/10.1609/aaai.v33i01.33012895.

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Embedding based models for knowledge base completion have demonstrated great successes and attracted significant research interest. In this work, we observe that existing embedding models all have their loss functions decomposed into atomic loss functions, each on a triple or an postulated edge in the knowledge graph. Such an approach essentially implies that conditioned on the embeddings of the triple, whether the triple is factual is independent of the structure of the knowledge graph. Although arguably the embeddings of the entities and relation in the triple contain certain structural information of the knowledge base, we believe that the global information contained in the embeddings of the triple can be insufficient and such an assumption is overly optimistic in heterogeneous knowledge bases. Motivated by this understanding, in this work we propose a new embedding model in which we discard the assumption that the embeddings of the entities and relation in a triple is a sufficient statistic for the triple’s factual existence. More specifically, the proposed model assumes that whether a triple is factual depends not only on the embedding of the triple but also on the embeddings of the entities and relations in a larger graph neighbourhood. In this model, attention mechanisms are constructed to select the relevant information in the graph neighbourhood so that irrelevant signals in the neighbourhood are suppressed. Termed locality-expanded neural embedding with attention (LENA), this model is tested on four standard datasets and compared with several stateof-the-art models for knowledge base completion. Extensive experiments suggest that LENA outperforms the existing models in virtually every metric.
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Chen, Samuel, Shengyi Xie, and Qingqiang Chen. "Integrated Embedding Approach for Knowledge Base Completion with CNN." Information Technology And Control 49, no. 4 (December 19, 2020): 622–42. http://dx.doi.org/10.5755/j01.itc.49.4.25366.

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To tackle specific problems in knowledge base completion such as computational complexity and complex relations or nodes with high indegree or outdegree, an algorithm called IEAKBC(short for Integrated Embedding Approach for Knowledge Base Completion) is proposed, in which entities and relations from triplets are first mapped into low-dimensional vector spaces, each original triplet represented in the form of 3-column, k dimensional matrix; then features from different relations are integrated into head and tail entities thus forming fused triplet matrices used as another input channel for convolution. In CNN feature maps are extracted by filters, concatenated and weighted for output scores to discern whether the original triplet holds or not. Experiments show that IEAKBC holds certain advantages over other models; when scaling up to relatively larger datasets, signs of superiority of IEAKBC stand out especially on relations with high cardinalities. At last we apply IEAKBC to a personalized search application, comparing its performance with strong baselines to verify its practicality in real environments.
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Malaviya, Chaitanya, Chandra Bhagavatula, Antoine Bosselut, and Yejin Choi. "Commonsense Knowledge Base Completion with Structural and Semantic Context." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (April 3, 2020): 2925–33. http://dx.doi.org/10.1609/aaai.v34i03.5684.

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Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC and ConceptNet) poses unique challenges compared to the much studied conventional knowledge bases (e.g., Freebase). Commonsense knowledge graphs use free-form text to represent nodes, resulting in orders of magnitude more nodes compared to conventional KBs ( ∼18x more nodes in ATOMIC compared to Freebase (FB15K-237)). Importantly, this implies significantly sparser graph structures — a major challenge for existing KB completion methods that assume densely connected graphs over a relatively smaller set of nodes.In this paper, we present novel KB completion models that can address these challenges by exploiting the structural and semantic context of nodes. Specifically, we investigate two key ideas: (1) learning from local graph structure, using graph convolutional networks and automatic graph densification and (2) transfer learning from pre-trained language models to knowledge graphs for enhanced contextual representation of knowledge. We describe our method to incorporate information from both these sources in a joint model and provide the first empirical results for KB completion on ATOMIC and evaluation with ranking metrics on ConceptNet. Our results demonstrate the effectiveness of language model representations in boosting link prediction performance and the advantages of learning from local graph structure (+1.5 points in MRR for ConceptNet) when training on subgraphs for computational efficiency. Further analysis on model predictions shines light on the types of commonsense knowledge that language models capture well.
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He, Lirong, Bin Liu, Guangxi Li, Yongpan Sheng, Yafang Wang, and Zenglin Xu. "Knowledge Base Completion by Variational Bayesian Neural Tensor Decomposition." Cognitive Computation 10, no. 6 (June 26, 2018): 1075–84. http://dx.doi.org/10.1007/s12559-018-9565-x.

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Zhao, Yu, Sheng Gao, Patrick Gallinari, and Jun Guo. "Knowledge base completion by learning pairwise-interaction differentiated embeddings." Data Mining and Knowledge Discovery 29, no. 5 (July 19, 2015): 1486–504. http://dx.doi.org/10.1007/s10618-015-0430-1.

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Dissertations / Theses on the topic "Knowledge Base Completion"

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Sertkaya, Baris. "Formal Concept Analysis Methods for Description Logics." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2008. http://nbn-resolving.de/urn:nbn:de:bsz:14-ds-1215598189927-85390.

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This work presents mainly two contributions to Description Logics (DLs) research by means of Formal Concept Analysis (FCA) methods: supporting bottom-up construction of DL knowledge bases, and completing DL knowledge bases. Its contribution to FCA research is on the computational complexity of computing generators of closed sets.
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Dunn-Norman, Shari. "A computational model and knowledge based system for well completion design." Thesis, Heriot-Watt University, 1990. http://hdl.handle.net/10399/1520.

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Sertkaya, Baris. "Formal Concept Analysis Methods for Description Logics." Doctoral thesis, Technische Universität Dresden, 2007. https://tud.qucosa.de/id/qucosa%3A23613.

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This work presents mainly two contributions to Description Logics (DLs) research by means of Formal Concept Analysis (FCA) methods: supporting bottom-up construction of DL knowledge bases, and completing DL knowledge bases. Its contribution to FCA research is on the computational complexity of computing generators of closed sets.
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Wei, Sheng-Lun, and 魏聖倫. "Chinese Relation Patterns Mining with High Coverage for Knowledge Base Acceleration and Completion." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/66660032512017215686.

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碩士
國立臺灣大學
資訊網路與多媒體研究所
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With the rapid development of the Internet in recent years, people can get infor-mation from it through different sources such as online news, social network, and fo-rums. A lot of information is created by people every day and some of them can be col-lected, comprehended, and turned into knowledge by human beings. Knowledge base is a way that people store those information with structural format. However, it’s hard to keep knowledge base up-to-date because of the wide gap between limited editors and numerous information of entities. Knowledge base acceleration is a critical issue which focus on accelerating the construction of knowledge base. In addition, relation patterns are useful for knowledge base acceleration. However, there are no resources available in languages beyond English. In this study, we present a workflow for building relation pattern extraction system with high coverage for knowledge base acceleration and knowledge base completion. Our properties is based on the properties in DBpedia knowledge base. We will discuss many details of our method including corpus pre-processing, instance retrieval, and pat-tern extraction. Finally, we evaluate our relation patterns by human annotators and dis-cuss features that may affect the performance of the relation patterns. With Chinese relation patterns, many related work can be utilized in Chinese by transferring from English environment to Chinese environment. Other languages may also use our method to build their own relation pattern resources.
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Win, Thein. "An assessment of the 'road-to-health-booklet' based on knowledge/perceptions of the clinic nurses and conduct a record review of the completion of the booklets." Thesis, 2016. http://hdl.handle.net/10539/22555.

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A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master in Public Health in the field of Rural Health. Johannesburg July 2016
INTRODUCTION Poor growth monitoring of children continues to be a major source of early death for children under five worldwide. The RTHB is an indispensable aid for under-five child development and health. AIM: To explore the knowledge and perceptions of the RTHB by clinic nurses, and to assess the completion of the RTHB booklets in the West Rand rural clinics. METHODS This study applied a quantitative and qualitative mixed method design. The first component is a retrospective records review of the 75 RTHBs of the children under-five. The second component is a qualitative study assessing the knowledge / perceptions of the new RTHBs by the nine nurses who provided child health services in the two rural clinics. Quantitative data was analysed using SPSS version 23 to conduct simple descriptive analysis for categorical variables. A thematic analysis was conducted on data collected through interviews with the clinic nurses. RESULTS The study found that only immunisation section was fully completed (100 percent). The weight-for-Age growth chart completion was excellent (81 percent). Most of the sections were less than 70 percent fully completed. The two growth charts (Lt/Ht X Age and Wt X Lt/Ht) were only around 30 percent fully completed. The Oral Health section was only seven percent fully completed. The qualitative interviews reveal six themes reflecting nurses perceptions of RTHB:: value of RTHB, barriers affecting effectiveness of RTHB, functions of RTHB, health system improvement, communication improvement and skills improvement. The value of the RTHB was based on the following: easy navigation; a comprehensive tool for child health information and child growth monitoring; clear scope; comprehensive infant feeding guidelines, and child referral tool. The barriers included poor completion, language, confidentiality, supply and demand, and limited note-making space. Suggested areas of improvement included: equipment availability for child growth monitoring; modifying sections of RTHB; providing mobile oral health services; completion of relevant sections by hospitals and cover change. CONCLUSION The study revealed that clinics from the West Rand District experienced problems in using the new RTHB, except for the Weight X Age Chart and Immunisation sections. The major problems were in the completion of child PMTCT/HIV section, the other two growth charts (Weight for Height and Height for Age growth charts) and referral for oral health examination. It is therefore essential to improve the RTHB utilisation in the West Rand District, since it is the cornerstone of the under-five child health care, which is closely related to mortality and morbidity of children. The District Clinical Specialist Team (DCST) should organise training, re-training, fire drills for the usage of RTHB.
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Books on the topic "Knowledge Base Completion"

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Ray, Sumantra (Shumone), Sue Fitzpatrick, Rajna Golubic, Susan Fisher, and Sarah Gibbings, eds. Monitoring. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199608478.003.0013.

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This chapter discusses the role and responsibilities of monitors/CRAs seeking to improve awareness of their role in a global industry becoming more and more technologically focused. How the role is changing through the introduction of risk based monitoring. Often the only liaison between the Sponsor and each study site, CRAs are crucial to the successful completion of a clinical trial and need to be armed with appropriate knowledge and training to conduct their visits. Successful monitoring requires experience, people skills, management ability and knowledge – of the protocol, CRFs, study drug/device, therapeutic area, regulations and SOPs. In this chapter this spectrum of roles and responsibilities is presented in a concise and understandable format. Questions such as: What type of person makes a good monitor? EDC and/or paper? How – and how often – to monitor? are addressed. There are helpful tips and strategies on a variety of topics, notably preparing a monitoring plan; how to identify and assess potential investigators; preparing for a Study Initiation Visit; eCRFs and remote monitoring; thorough Source Data Verification; how to report monitoring visits plus example checklists associated with site visits and review of the Investigator Site File. The guidance provided in this chapter should help CRAs perform their essential role in encouraging good, high quality research - and provide an insight into the CRA role to those whose work is being monitored.
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Marjot, Thomas, Colleen McGregor, Tim Ambrose, Simon Travis, Aminda De Silva, and Jeremy Cobbold, eds. Best of Five MCQS for the European Specialty Examination in Gastroenterology and Hepatology. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198834373.001.0001.

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This question book is designed to assist in preparations for the European Specialty Examination in Gastroenterology and Hepatology (ESEGH). Completing this examination demonstrates that sufficient knowledge has been acquired to fulfil the requirements of a specialist in gastroenterology and hepatology, according to a curriculum agreed upon across Europe. This preparation book adopts the same ‘Best of Five’ question format used in the ESEGH. Furthermore, it covers the breadth of the curriculum, and its composition has been designed to exactly match the relative proportion of questions on each topic area found in the examination. Each of the 300 questions contained in the book is accompanied by an answer, a set of succinct bullet points of key ‘take-home’ messages and a short summary of the relevant background, evidence base, and up-to-date European guidelines. The book ends with a chapter of 50 questions designed to act as a mock examination for use in the final stages of preparation.
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Book chapters on the topic "Knowledge Base Completion"

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He, Wenqiang, Yansong Feng, Lei Zou, and Dongyan Zhao. "Knowledge Base Completion Using Matrix Factorization." In Web Technologies and Applications, 256–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25255-1_21.

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Kolyvakis, Prodromos, Alexandros Kalousis, and Dimitris Kiritsis. "Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion." In The Semantic Web, 199–214. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49461-2_12.

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Guo, Shu, Boyang Ding, Quan Wang, Lihong Wang, and Bin Wang. "Knowledge Base Completion via Rule-Enhanced Relational Learning." In Communications in Computer and Information Science, 219–27. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3168-7_22.

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Baader, Franz, and Barış Sertkaya. "Usability Issues in Description Logic Knowledge Base Completion." In Formal Concept Analysis, 1–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01815-2_1.

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Huang, Yong, and Zhichun Wang. "Knowledge Base Completion by Learning to Rank Model." In Communications in Computer and Information Science, 1–6. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-7359-5_1.

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He, Wenqiang, Yansong Feng, and Dongyan Zhao. "Improving Knowledge Base Completion by Incorporating Implicit Information." In Semantic Technology, 141–53. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31676-5_10.

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Huang, Wenhao, Ge Li, and Zhi Jin. "Improved Knowledge Base Completion by the Path-Augmented TransR Model." In Knowledge Science, Engineering and Management, 149–59. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63558-3_13.

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Cerezo-Costas, Héctor, and Manuela Martín-Vicente. "Relation Extraction for Knowledge Base Completion: A Supervised Approach." In Semantic Web Challenges, 52–66. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00072-1_5.

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Wang, Zhichun, and Yong Huang. "Knowledge Base Completion by Inference from Both Relational and Literal Facts." In Advances in Knowledge Discovery and Data Mining, 501–13. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16142-2_39.

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Oulabi, Yaser, and Christian Bizer. "Using Weak Supervision to Identify Long-Tail Entities for Knowledge Base Completion." In Lecture Notes in Computer Science, 83–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33220-4_7.

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Conference papers on the topic "Knowledge Base Completion"

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Li, Xiang, Aynaz Taheri, Lifu Tu, and Kevin Gimpel. "Commonsense Knowledge Base Completion." In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/p16-1137.

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Wei, Zhuoyu, Jun Zhao, Kang Liu, Zhenyu Qi, Zhengya Sun, and Guanhua Tian. "Large-scale Knowledge Base Completion." In CIKM'15: 24th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2806416.2806513.

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Saito, Itsumi, Kyosuke Nishida, Hisako Asano, and Junji Tomita. "Commonsense Knowledge Base Completion and Generation." In Proceedings of the 22nd Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/k18-1014.

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Kadlec, Rudolf, Ondrej Bajgar, and Jan Kleindienst. "Knowledge Base Completion: Baselines Strike Back." In Proceedings of the 2nd Workshop on Representation Learning for NLP. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/w17-2609.

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Kocijan, Vid, and Thomas Lukasiewicz. "Knowledge Base Completion Meets Transfer Learning." In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-main.524.

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Sudhahar, Saatviga, Andrea Pierleoni, and Ian Roberts. "Reasoning Over Paths via Knowledge Base Completion." In Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-5320.

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Xie, Qizhe, Xuezhe Ma, Zihang Dai, and Eduard Hovy. "An Interpretable Knowledge Transfer Model for Knowledge Base Completion." In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/p17-1088.

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West, Robert, Evgeniy Gabrilovich, Kevin Murphy, Shaohua Sun, Rahul Gupta, and Dekang Lin. "Knowledge base completion via search-based question answering." In the 23rd international conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2566486.2568032.

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Wang, Quan, Jing Liu, Yuanfei Luo, Bin Wang, and Chin-Yew Lin. "Knowledge Base Completion via Coupled Path Ranking." In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/p16-1124.

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Komninos, Alexandros, and Suresh Manandhar. "Feature-Rich Networks for Knowledge Base Completion." In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/p17-2051.

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Reports on the topic "Knowledge Base Completion"

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Baader, Franz, Bernhard Ganter, Ulrike Sattler, and Barış Sertkaya. Completing Description Logic Knowledge Bases using Formal Concept Analysis. Aachen University of Technology, 2006. http://dx.doi.org/10.25368/2022.155.

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We propose an approach for extending both the terminological and the assertional part of a Description Logic knowledge base by using information provided by the assertional part and by a domain expert. The use of techniques from Formal Concept Analysis ensures that, on the one hand, the interaction with the expert is kept to a minimum, and, on the other hand, we can show that the extended knowledge base is complete in a certain sense.
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Peñaloza, Rafael, and Anni-Yasmin Turhan. Completion-based computation of most specific concepts with limited role-depth for EL and Prob-EL⁰¹. Technische Universität Dresden, 2010. http://dx.doi.org/10.25368/2022.176.

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In Description Logics the reasoning service most specific concept (msc) constructs a concept description that generalizes an ABox individual into a concept description. For the Description Logic EL the msc may not exist, if computed with respect to general EL-TBoxes or cyclic ABoxes. However, it is still possible to find a concept description that is the msc up to a fixed role-depth, i.e. with respect to a maximal nesting of quantifiers. In this report we present a practical approach for computing the roledepth bounded msc, based on the polynomial-time completion algorithm for EL. We extend these methods to Prob-EL⁰¹c , which is a probabilistic variant of EL. Together with the companion report [9] this report devises computation methods for the bottom-up construction of knowledge bases for EL and Prob-EL⁰¹c .
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Yusrina, Asri, Ulfah Alifia, Shintia Revina, Rezanti Putri Pramana, and Luhur Bima. Is the Game Worth the Candle? Examining the Effectiveness of Initial Teacher Education in Indonesia. Research on Improving Systems of Education (RISE), August 2022. http://dx.doi.org/10.35489/bsg-rise-wp_2022/106.

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An impactful teacher education programme equips teachers with knowledge and skills to improve their effectiveness. Empirical findings on the effectiveness of teacher preparation programmes show that the accountability of institutions and teachers should not only be based on the knowledge or skills produced but also on student learning. Our study aims to evaluate the effectiveness of a pre-service teacher education programme in Indonesia, known as Pendidikan Profesi Guru Prajabatan or PPG. PPG is a one-year full-time programme in addition to four years of undergraduate teacher education (Bachelor of Education). PPG graduate teachers pass a selection process and receive a teaching certificate upon completion of the programme. We use mixed methods to understand the differences in the outcome of PPG graduates majoring in primary school teacher education to their counterparts who did not attend PPG. To estimate the impact of PPG, we exploit the combination of rules and events in the selection process which allows us to estimate the impact of PPG on teacher performance using fuzzy regression discontinuity design (RDD). Once we attest to the validity of the fuzzy RDD, we find that PPG has no impact on a teacher’s professional knowledge and student outcomes in numeracy and literacy. We argue that this is due to the ineffective selection mechanism in distinguishing the PPG and the comparison group. We conclude that as an initial teacher training programme, PPG did not improve teacher effectiveness. Despite incorporating best practices from effective teacher training into the programme design, PPG does not appear capable of producing a higher-quality teacher.
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Rarasati, Niken, and Rezanti Putri Pramana. Giving Schools and Teachers Autonomy in Teacher Professional Development Under a Medium-Capability Education System. Research on Improving Systems of Education (RISE), January 2023. http://dx.doi.org/10.35489/bsg-rise-ri_2023/050.

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A mature teacher who continuously seeks improvement should be recognised as a professional who has autonomy in conducting their job and has the autonomy to engage in a professional community of practice (Hyslop-Margison and Sears, 2010). In other words, teachers’ engagement in professional development activities should be driven by their own determination rather than extrinsic sources of motivation. In this context, teachers’ self-determination can be defined as a feeling of connectedness with their own aspirations or personal values, confidence in their ability to master new skills, and a sense of autonomy in planning their own professional development path (Stupnisky et al., 2018; Eyal and Roth, 2011; Ryan and Deci, 2000). Previous studies have shown the advantages of providing teachers with autonomy to determine personal and professional improvement. Bergmark (2020) found that giving teachers the opportunity to identify areas of improvement based on teaching experience expanded the ways they think and understand themselves as teachers and how they can improve their teaching. Teachers who plan their own improvement showed a higher level of curiosity in learning and trying out new things. Bergmark (2020) also shows that a continuous cycle of reflection and teaching improvement allows teachers to recognise that the perfect lesson does not exist. Hence, continuous reflection and improvement are needed to shape the lesson to meet various classroom contexts. Moreover, Cheon et al. (2018) found that increased teacher autonomy led to greater teaching efficacy and a greater tendency to adopt intrinsic (relative to extrinsic) instructional goals. In developed countries, teacher autonomy is present and has become part of teachers’ professional life and schools’ development plans. In Finland, for example, the government is responsible for providing resources and services that schools request, while school development and teachers’ professional learning are integrated into a day-to-day “experiment” performed collaboratively by teachers and principals (Niemi, 2015). This kind of experience gives teachers a sense of mastery and boosts their determination to continuously learn (Ryan and Deci, 2000). In low-performing countries, distributing autonomy of education quality improvement to schools and teachers negatively correlates with the countries’ education outcomes (Hanushek et al., 2011). This study also suggests that education outcome accountability and teacher capacity are necessary to ensure the provision of autonomy to improve education quality. However, to have teachers who can meet dynamic educational challenges through continuous learning, de Klerk & Barnett (2020) suggest that developing countries include programmes that could nurture teachers’ agency to learn in addition to the regular content and pedagogical-focused teacher training materials. Giving autonomy to teachers can be challenging in an environment where accountability or performance is measured by narrow considerations (teacher exam score, administrative completion, etc.). As is the case in Jakarta, the capital city of Indonesia, teachers tend to attend training to meet performance evaluation administrative criteria rather than to address specific professional development needs (Dymoke and Harrison, 2006). Generally, the focus of the training relies on what the government believes will benefit their teaching workforce. Teacher professional development (TPD) is merely an assignment for Jakarta teachers. Most teachers attend the training only to obtain attendance certificates that can be credited towards their additional performance allowance. Consequently, those teachers will only reproduce teaching practices that they have experienced or observed from their seniors. As in other similar professional development systems, improvement in teaching quality at schools is less likely to happen (Hargreaves, 2000). Most of the trainings were led by external experts or academics who did not interact with teachers on a day-to-day basis. This approach to professional development represents a top-down mechanism where teacher training was designed independently from teaching context and therefore appears to be overly abstract, unpractical, and not useful for teachers (Timperley, 2011). Moreover, the lack of relevancy between teacher training and teaching practice leads to teachers’ low ownership of the professional development process (Bergmark, 2020). More broadly, in the Jakarta education system, especially the public school system, autonomy was never given to schools and teachers prior to establishing the new TPD system in 2021. The system employed a top-down relationship between the local education agency, teacher training centres, principals, and teachers. Professional development plans were usually motivated by a low teacher competency score or budgeted teacher professional development programme. Guided by the scores, the training centres organised training that could address knowledge areas that most of Jakarta's teachers lack. In many cases, to fulfil the quota as planned in the budget, the local education agency and the training centres would instruct principals to assign two teachers to certain training without knowing their needs. Realizing that the system was not functioning, Jakarta’s local education agency decided to create a reform that gives more autonomy toward schools and teachers in determining teacher professional development plan. The new system has been piloted since November 2021. To maintain the balance between administrative evaluation and addressing professional development needs, the new initiative highlights the key role played by head teachers or principals. This is based on assumption that principals who have the opportunity to observe teaching practice closely could help teachers reflect and develop their professionalism. (Dymoke and Harrison, 2006). As explained by the professional development case in Finland, leadership and collegial collaboration are also critical to shaping a school culture that could support the development of professional autonomy. The collective energies among teachers and the principal will also direct the teacher toward improving teaching, learning, and caring for students and parents (Hyslop-Margison and Sears, 2010; Hargreaves, 2000). Thus, the new TPD system in Jakarta adopts the feature of collegial collaboration. This is considered as imperative in Jakarta where teachers used to be controlled and join a professional development activity due to external forces. Learning autonomy did not exist within themselves. Hence, teachers need a leader who can turn the "professional development regulation" into a culture at schools. The process will shape teachers to do professional development quite autonomously (Deci et al., 2001). In this case, a controlling leadership style will hinder teachers’ autonomous motivation. Instead, principals should articulate a clear vision, consider teachers' individual needs and aspirations, inspire, and support professional development activities (Eyal and Roth, 2011). This can also be called creating a professional culture at schools (Fullan, 1996). In this Note, we aim to understand how the schools and teachers respond to the new teacher professional development system. We compare experience and motivation of different characteristics of teachers.
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