This Writing Activity with Writing Analytics (WAWA) was developed as part of the Academic Writing Analytics project at the University of Technology Sydney’s Connected Intelligence Centre.
The focus is on academic rhetorical moves typically made in scientific, technological and social science articles. AcaWriter highlights these moves in order to help students evaluate their writing and improve the successive drafts with special attention to rhetorical moves. Arts and humanities genres are more variable, and less well tested. The parser is tuned to how ideas are being proposed, referred to, contrasted, and so forth.
The italicised text in the examples below shows a familiar type of move, in which the authors signal their intent:
“The purpose of this article is to develop the idea that the procedures in any given classroom or laboratory exercise should be definitely determined by the specific aim, which the instructor has in mind to accomplish.”
“The perspective I shall use in this essay relies heavily on the view of professionalization presented in Andrew Abbott’s brilliant study, The System of Professions (Abbott 1988).”
“This paper explores social practices of propagating ‘memes’ (pronounced,‘meems’) as a dimension of cultural production and transmission within internet environments.”
In most disciplines, readers (especially reviewers) would be surprised if there were no contrasting moves, e.g.
“We think it timely, with the rising popularity of data science, to call attention to some of the problems that can infiltrate a field like LA if we do not pay careful attention to our underlying assumptions.”
“With an absence of detailed work on masculinities and sport in South African primary schools (for an exception, see Bhana 2002) this paper goes some way towards addressing the issues around young boys’ developing relationship with sport.”
Textual Features: The set of rhetorical moves identified by AcaWriter are as follows:
Background/consensus information / prior work, e.g. using constructions such as:
Recent studies indicate …
the previously proposed …
is universally accepted …
Summarising/signalling the author’s/paper’s goals
The goal of this study …
Here, we show …
Altogether, our results … indicate
Emphasis to highlight significance / key ideas
studies … have provided important advances
Knowledge … is crucial for … understanding
valuable information … from studies
Novelty of some sort / improvements in ideas/contributions
… new insights provide direct evidence …
… we suggest a new … approach …
… results define a novel role …
Contrasting ideas, tension or critical insight
… unorthodox view resolves … paradoxes …
In contrast with previous hypotheses …
… inconsistent with past findings …
Surprising or unexpected findings
We have recently observed … surprisingly
We have identified … unusual
The recent discovery … suggests intriguing roles
Open questions / gaps in knowledge
… little is known …
… role … has been elusive
Current data is insufficient …
Trend / generalisation / tendency
… emerging as a promising approach
our understanding of… has grown exponentially …
… growing recognition of the importance …
Attitude / stance
This Genre Profile provides the foundation for others, tuning it for specific pedagogical goals and contexts — browse the Resources menu for Law, Accounting and Research Abstracts.
Analytics Genre Profile
Analytical Writing (Standard)
This describes the Genre module in AcaWriter that has been developed to support this activity.
License: Creative Commons BY-SA 4.0
Developed by: Ágnes Sándor (Naver Labs Europe) and Simon Buckingham Shum (University of Technology Sydney)
Based on: None
Purpose: Highlights sentences that appear to show hallmarks of the academic rhetorical moves typically made in scientific, technological and social science articles. Arts and humanities genres are less well tested. These moves have been found also to apply in non-research genres, such as literature reviews, persuasive essays, and other forms of analytical, argumentative writing.
These moves are tagged at the sentence level. There can be more than one rhetorical move in a sentence.
AcaWriter’s Analytical Report highlights sentences that have been classified as any of the above types, and appears as shown in the example below:
The original scholarship underpinning this was conducted by Ágnes Sándor, from the linguistic analysis of many research publications in biomedical sciences and social sciences. Example research papers include:
Ágnes Sándor and Anita de Waard (2012). Identifying Claimed Knowledge Updates in Biomedical Research Articles. Proceedings of the Workshop on Detecting Structure in Scholarly Discourse, 50th Annual Meeting of the Association for Computational Linguistics, Jeju, Republic of Korea, 8-14 July, 2012.
Ágnes Sándor & Angela Vorndran (2010). Extracting relevant messages from social science research papers for improving relevance of retrieval. Workshop on Natural Language Processing Tools Applied to Discourse Analysis in Psychology, Buenos Aires, 10–14 May 2010.
Frédérique Lisacek, Christine Chichester, Aaron Kaplan, & Ágnes Sandor. (2005). Discovering paradigm shift patterns in biomedical abstracts: application to neurodegenerative diseases. In Proceedings of the First International Symposium on Semantic Mining in Biomedicine (SMBM) (pp. 41-50).
Ágnes Sándor (2007). Modeling metadiscourse conveying the author’s rhetorical strategy in biomedical research abstracts. Revue française de linguistique appliquée, 2007/2 (Vol. XII), p. 97-108.
Subsequently, this work was tested and extended in a range of contexts:
Focus: Scaffolding the learning design workflow with a web-based tool called AWA-Tutor:
Antonette Shibani, Simon Knight, Simon Buckingham Shum and Philippa Ryan (2017). Design and Implementation of a Pedagogic Intervention Using Writing Analytics. In Proceedings of the 25th International Conference on Computers in Education. New Zealand: Asia-Pacific Society for Computers in Education.
Focus: Software demo movie:
Antonette Shibani (2018). AWA-Tutor: A Platform to Ground Automated Writing Feedback in Robust Learning Design (Demo). In Companion Proceedings of the Eighth International Conference on Learning Analytics & Knowledge (LAK ’18), Sydney, Australia.
Focus: Civil Law undergraduate essays
Knight, S., Buckingham Shum, S., Ryan, P., Sándor, Á., & Wang, X. (2017). Academic Writing Analytics for Civil Law: Participatory Design Through Academic and Student Engagement. International Journal of Artificial Intelligence in Education, 28, (1), 1-28.
Focus: English literature student essays
Simsek, Duygu; Sandor, Agnes; Buckingham Shum, Simon; Ferguson, Rebecca; De Liddo, Anna and Whitelock, Denise. (2015). Correlations between automated rhetorical analysis and tutors’ grades on student essays. In: Proceedings of the Fifth International Conference on Learning Analytics & Knowledge, ACM, pp.355-359.
Focus: educational data science literature
Taibi, Davide; Sandor, Agnes; Simsek, Duygu; Buckingham Shum, Simon; De Liddo, Anna and Ferguson, Rebecca. (2013). Visualizing the LAK/EDM literature using combined concept and rhetorical sentence extraction. In: Proceedings of the LAK Data Challenge, 3rd Int. Conf. on Learning Analytics and Knowledge (LAK ’13), 8-12 Apr 2013, Leuven, Belgium.
Focus: educational R&D project final reports
De Liddo, A., Sándor, Á. and Buckingham Shum, S. (2012). Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study. Computer Supported Cooperative Work, 21, (4-5), pp. 417-448, DOI: 10.1007/s10606-011-9155-x.
Focus: relationship to other modelling approaches
de Waard, A.; Buckingham Shum, S.; Carusi, A.; Park, J.; Samwald, M. and Sándor, Á. (2009). Hypotheses, evidence and relationships: The HypER approach for representing scientific knowledge claims. Workshop on Semantic Web Applications in Scientific Discourse, 8th International Semantic Web Conference. Lecture Notes in Computer Science, Springer Verlag: Berlin, 26 Oct 2009, Washington DC.