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Gist of LAK 22 paper

Last month I attended the 25th International Conference on Computers in Education ICCE 2017 at Christchurch, New Zealand, organised by the Asia-Pacific Society for Computers in Education (APSCE). It was the first time I attended this conference, although I have heard of it previously when I was working in NIE, Singapore. Overall, it was a ...

I’ve recently been consolidating a lot of R code from different parts of my analysis into one file. I wanted to add good documentation and explanation of results and interpretations along with my code to make sense of it later. I came across this option of creating dynamic reports that can combine our code, custom text ...

What is CKEditor CKEditor is an open source, customizable web text editor that can be integrated to our webpages. It can be used in three different modes (Article editor, Document editor and Inline editor) for content creation. I was looking for a web editor like Google doc using which I can collect text data from students (but not ...

Last week I attended a talk in UTS by Professor Witold Pedrycz on the essentials of effective publishing and how to disseminate research results. He is a well known Professor in the field of Computational Intelligence with  great credentials (Editor-in-chief of very high impact journals, 40,000+ citations etc.). In early stages of PhD and research, we tend to ...

Alert – Long post! In this post, I’m presenting a summary of my review on tools for automatically analyzing rhetorical structures from academic writing. The tools considered are designed to cater to different users and purposes. AWA and RWT aim to provide feedback for improving students’ academic writing. Mover and SAPIENTA on the other hand, are ...

Reference: Cotos, E., & Pendar, N. (2016). Discourse classification into rhetorical functions for AWE feedback. calico journal, 33(1), 92. Background: Computational techniques can be exploited to provide individualized feedback to learners on writing. Genre analysis on writing to identify moves (communicative goal) and steps (rhetorical functions to help achieve the goal) . Natural language processing (NLP) and machine learning categorization ...

Reference: Simsek, D., Buckingham Shum, S., Sandor, A., De Liddo, A., & Ferguson, R. (2013). XIP Dashboard: visual analytics from automated rhetorical parsing of scientific metadiscourse. In: 1st International Workshop on Discourse-Centric Learning Analytics, 8 Apr 2013, Leuven, Belgium. Background: Learners should have the ability to critically evaluate research articles and be able to identify the claims ...

Reference: Liakata, M., Saha, S., Dobnik, S., Batchelor, C., & Rebholz-Schuhmann, D. (2012). Automatic recognition of conceptualization zones in scientific articles and two life science applications. Bioinformatics, 28(7), 991-1000. Background: Scientific discourse analysis helps in distinguishing the nature of knowledge in research articles (facts, hypothesis, existing and new work). Annotation schemes vary across disciplines in scope and granularity. Purpose: To build ...

Reference: Wu, J. C., Chang, Y. C., Liou, H. C., & Chang, J. S. (2006, July). Computational analysis of move structures in academic abstracts. In Proceedings of the COLING/ACL on Interactive presentation sessions (pp. 41-44). Association for Computational Linguistics. Background: Swales pattern for research articles: Introduction, Methods, Results, Discussion (IMRD) and Creating a Research Space (CARS) model. Studying the rhetorical ...

Reference: Wong, P. C., Cowley, W., Foote, H., Jurrus, E., & Thomas, J. (2000). Visualizing sequential patterns for text mining. In Information Visualization, 2000. InfoVis 2000. IEEE Symposium on (pp. 105-111). IEEE. Background: Mining Sequential patterns aims to identify recurring patterns from data over a period of time. A pattern is a finite series of elements from the same domain A ...