ARB 307 - Language Acquisition

To teach the theories of  language acquisition, to make them comparable and exemplify, to define the stages of language development and language acquisition process and language acquisition and learning-processes, to have information about the basic features of the language, especially the first and second language, and to discuss how the learning takes place in humans. Also, the course focuses on comunication disorders; its reasons and solutions.

Developmental stages in mother tongue acquisition, morpho-syntactic development stages in the second language, second language acquisition processes, learner characteristics in second language acquisition and individual differences in final acquisition (e.g. personality influence, language ability, intelligence, age of acquisition, motivation and attitude, learner preferences and beliefs), the difference between second language and foreign language learning contexts, multiple intelligences theory.

Mukaddima fi el-lugawiyyat el-mu'asira, Shihde Fari' and others, Wael publishings, Amman, 2006

Ta'lim el_luga Arabiyya li_gayri nnatigin biha ennazariyyetu vetabiik, Ali Ahmet Medkur and Iman Ahmed Hureydi, Cairo

El-Merjéı Menaheg Ta'leem el-luga al-Arabiyye Linatin bi Lugaat Ukhra, Ali Medkur, Rushdie Ahmed Tuayme, Iman Ahmed Hureydi, Cairo, 2010

• [1] Bahdanau, D., Cho, K., Bengio, Y., "Neural machine translation by jointly learning to align and translate", International Conference on Learning Representations (ICLR), Conference, USA, 1- 15, (2015).
• [2] Luong, M.T., Pham, H., Manning, C.D., "Effective approaches to attention-based neural machine translation", Empirical Methods in Natural Language Processing (EMNLP), Conference, Portugal, 1412-1421, (2015).
• [3] Yadav, V., Bethard, S., "A survey on recent advances in named entity recognition from deep learning models", Proceedings of the 27th International Computational Linguistics, Conference, USA, 2145–2158, (2019).
• [4] Singh, S., Mahmood, A., "The NLP Cookbook: Modern Recipes for Transformer Based Deep Learning Architectures", IEEE Access, 4: 68675-68702, (2021).
• [5] Kang, Y., Cai, Z., Tan, C. W., Huang, Q., Liu H., "Natural language processing (NLP) in management research: A literature review", Journal of Management Analytics, 7(2): 139-172 (2020).
• [6] Nemeshaev, S., Barykin, L., Dadteev, K., "Selection of experts for scientific and technical expertise based on semantic search", Procedia Computer Science, 190: 643-646, (2021).
• [7] Ott, M., Edunov, S., Grangier, D., Auli, M., "Scaling neural machine translation", Proceedings of the Machine Translation, Conference, USA, 1: 1-9, (2018).
• [8] Wang, H., Wu, H., He, Z., Huang, L., Church, K.W., "Progress in Machine Translation", Engineering, 3: 1-19, (2021).
• [9] Alomari, A., Idris, N., Sabri, A. Q. Alsmadi, I., "Deep Reinforcement and Transfer Learning for Abstractive Text Summarization: A Review", Computer Speech & Language, 71: 1-43, (2021).
• [10] Merchant, K., Pande, Y., "Nlp based latent semantic analysis for legal text summarization", International Conference on Advances in Computing, Communications and Informatics (ICACCI), India, 1803-1807, (2018).
• [11] Zhang, Y., Tuo, M., Yin, Q., Qi, L., Wang, X., Liu, T., "Keywords extraction with deep neural network model", Neurocomputing, 383: 113-121, (2020).
• [12] Firoozeh, N., Nazarenko, A., Alizon, F., Daille, B., "Keyword extraction: Issues and methods", Natural Language Engineering, 26(3): 259-291, (2020).
• [13] Yi, J., Nasukawa, T., Bunescu, R., Niblack, W., "Sentiment analyzer: “Extracting sentiments about a given topic using natural language processing techniques", IEEE Data Mining, Conference, USA, 1-8, (2003).
• [14] Ritter, A., Clark, S., Etzioni, O., "Named entity recognition in tweets: an experimental study", Proceedings of Empirical Methods in Natural Language Processing, Conference, UK, 1524-1534, (2011).
• [15] Sharma, S., Srinivas, PY., Balabantaray, R., "Emotion detection using online machine learning method and TLBO on mixed script", In Language Resources and Evaluation Workshop (LREC), 47-51, Slovenia, (2016).
• [16] Seal, D., Roy, UK., Basak, R., "Sentence-level emotion detection from text based on semantic rules", In Information and Communication Technology for Sustainable Development, 933: 423-430, Springer, Singapore, (2019).
• [17] Chrupała, G., "Text segmentation with character-level text embeddings", Workshop on Deep Learning for Audio, Speech and Language Processing (ICML), 1-5, USA, (2013).
• [18] Nguyen, H., Calantone, R., Krishnan, R., "Influence of social media emotional word of mouth on institutional investors decisions and firm value", Management Science, 66(2): 503-529, (2019).
• [19] Dyer, T., Lang, M., Stice-Lawrence, L., "The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation", Journal of Accounting and Economics, 64(2-3): 221-245, (2017).
• [20] Calomiris, C. W., Mamaysky, H., "How news and its context drive risk and returns around the world", Journal of Financial Economics, 133(2): 299-336, (2019).
• [21] Froot, K., Kang, N., Ozik, G., Sadka, R., "What do measures of real-time corporate sales say about earnings surprises and post-announcement returns", Journal of Financial Economics, 125(1): 143-162, (2017).
• [22] Wu, L., Lou, B., Hitt, L., "Data analytics supports decentralized innovation", Management Science, 65(10): 4451-4469, (2018).
• [23] Ghose, A., Ipeirotis, P.G., Li, B., "Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content", Marketing Science, 31(3): 369-371, (2012).
• [24] Ramaswamy, S., DeClerck, N., "Customer perception analysis using deep learning and NLP", Procedia Computer Science, 140: 170-178, (2018).
• [25] Barlow, M. A., Verhaal, J. C., Angus, R. W., "Optimal distinctiveness, strategic categorization, and product market entry on the Google Play app platform", Strategic Management Journal, 40(8): 1219-1242, (2019).
• [26] Zhou, Y., Zheng, X., Hsieh, C. J., Chang, K. W., Huang, X., "Defense against adversarial attacks in nlp via dirichlet neighborhood ensemble" Association for Computational Linguistics (ACL), Conference, China, 2(3): 1-12, (2020).
• [27] Dalton, A., Aghaei, E., Al-Shaer, E., Bhatia, A., Castillo, E., Cheng, Z., Dhaduvai, S., Duan, Q., Hebenstreit, B., Islam, M. M., Karimi, Y., "Proceedings of the Workshop on Social Threats in Online Conversations: Understanding and Management, (STOC)", 1-8, France, (2020).
• [28] Ray, A., Bala, P. K., Kumar, R., "An NLP-SEM approach to examine the gratifications affecting user’s choice of different e-learning providers from user tweets", Journal of Decision Systems, 30(4): 439-445, (2020).
• [29] Pan. P., Chen, Y., "Automatic subject classification of public messages in e-government affairs", Data and Information Management, 5(3): 336-347, (2021).
• [30] Tvardik, N., Kergourlay, I., Bittar, A., Segond, F., Darmoni, S., Metzger, M. H., "Accuracy of using natural language processing methods for identifying healthcare-associated infections", International Journal of Medical Informatics, 117: 96-102, (2018).
• [31] Jain, K., Prajapati, V., "NLP/Deep Learning Techniques in Healthcare for Decision Making", Primary Health Care: Open Access, 11(3): 373-380, (2021).
• [32] Carchiolo, V., Longheu, A., Reitano, G., Zagarella, L., "Medical prescription classification: a NLP-based approach", Federated Conference on Computer Science and Information Systems (FedCSIS), Germany, 605-609, (2019).
• [33] Yu J, Luo G, Xiao T, Zhong Q, Wang Y, Feng W, Luo J, Wang C, Hou L, Li J, Liu Z. “MOOCCube: a large-scale data repository for NLP applications in MOOCs”, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 3135-3142, (2020).
• [34] Alblawi, AS., Alhamed, A. A., "Big data and learning analytics in higher education: Demystifying variety, acquisition, storage, NLP and analytics", IEEE Conference on Big Data and Analytics (ICBDA), Malaysia, 124-129, (2017).
• [35] Lalwani, T., Bhalotia, S., Pal, A., Rathod, V., Bisen, S., "Implementation of a Chatbot System using AI and NLP", International Journal of Innovative Research in Computer Science & Technology (IJIRCST), 6(3): 26-30, (2018).
• [36] Häse, F., Roch, L. M., Aspuru-Guzik, A., "Next-generation experimentation with self-driving laboratories", Trends in Chemistry, 1(3): 282-291, (2019).
• [37] Chandio, J. A., Talpur, M. S. H., Abro, A. A., Bux, H., Khokhar, N. U. A. A., Shah, A. A., Saima, M., “Study Of Customers Perception About Shopping Trend Involving E-Commerce: A Comparative Study”, Turkish Online Journal of Qualitative Inquiry, 12(8): 5415-5424, (2021).
• [38] Abro, A. A., Khan, A. A., Talpur, M. S. H., Kayijuka, I., “Machine Learning Classifiers: A Brief Primer”, University of Sindh Journal of Information and Communication Technology, 5(2): 63-68, (2021)
• [39] Abro, A. A., Taşci, E., Aybars, U. G., "A Stacking-based Ensemble Learning Method for Outlier Detection", Balkan Journal of Electrical and Computer Engineering, 8(2): 181-185, (2020).
• [40] Abro, A. A., Yimer, M. A., Bhatti, Z., "Identifying the Machine Learning Techniques for Classification of Target Datasets", Sukkur IBA Journal of Computing and Mathematical Sciences, 4(1): 45-52, (2020).
• [41] Abro, A. A., "Vote-Based: Ensemble Approach", Sakarya University Journal of Science, 25(3): 858-866, (2021).
• [42] Abro, A. A., Siddique, W. A., Talpur, M. S. H., Jumani, A. K., Yaşar, E., “A combined approach of base and meta learners for hybrid system”, Turkish Journal of Engineering, 7(1): 25-32, (2023).
• AN OVERVIEW OF SECOND LANGUAGE ACQUISITION (RESEARCH) AND DIRECTED FIELDS OF SECOND LANGUAGE ACQUISITION, Dilek PEÇENEK.

Students must have %70 attendance whole the term to be able to entered the final exam.Student must have 50 point to pass the final exam.