A collaborative project as a learning opportunity for mathematics teachers

This paper analyses the evolution of Maria, a mathematics teacher involved in a long term collaborative project together with a researcher and two other teachers. The study aimed to understand teaching practices and to develop richer classroom communication processes. It follows a qualitative-interpretative approach, with data gathered through recording of meetings and interviews. We discuss to what extent this project became relevant for the professional practice of Maria. The results indicate the potential of collaboration to understand communication phenomena in the classroom, putting practices under scrutiny and developing richer communication interaction patterns between teacher and students

Inferring User Needs and Tasks from User Interactions

The need for search often arises from a broad range of complex information needs or tasks (such as booking travel, buying a house, etc.) which lead to lengthy search processes characterised by distinct stages and goals. While existing search systems are adept at handling simple information needs, they offer limited support for tackling complex tasks. Accurate task representations could be useful in aptly placing users in the task-subtask space and enable systems to contextually target the user, provide them better query suggestions, personalization and recommendations and help in gauging satisfaction. The major focus of this thesis is to work towards task based information retrieval systems - search systems which are adept at understanding, identifying and extracting tasks as well as supporting user’s complex search task missions. This thesis focuses on two major themes: (i) developing efficient algorithms for understanding and extracting search tasks from log user and (ii) leveraging the extracted task information to better serve the user via different applications. Based on log analysis on a tera-byte scale data from a real-world search engine, detailed analysis is provided on user interactions with search engines. On the task extraction side, two bayesian non-parametric methods are proposed to extract subtasks from a complex task and to recursively extract hierarchies of tasks and subtasks. A novel coupled matrix-tensor factorization model is proposed that represents user based on their topical interests and task behaviours. Beyond personalization, the thesis demonstrates that task information provides better context to learn from and proposes a novel neural task context embedding architecture to learn query representations. Finally, the thesis examines implicit signals of user interactions and considers the problem of predicting user’s satisfaction when engaged in complex search tasks. A unified multi-view deep sequential model is proposed to make query and task level satisfaction prediction

Establishing User Requirements for a Recommender System in an Online Union Catalogue: an Investigation of WorldCat.org

This project, undertaken in collaboration with OCLC, aimed to investigate the potential role of recommendations within WorldCat, the publicly accessible union catalogue of libraries participating in the OCLC global cooperative. The goal of the project was a set of conceptual design guidelines for a WorldCat.org recommender system, based on a comprehensive understanding of the systems users and their needs. Taking a mixed-methods approach, the investigation consisted of four phases. Phase one consisted of twenty-one focus groups with key user goups held in three locations; the UK, the US, and Australia and New Zealand. Phase 2 consisted of a pop-up survey implemented on WorldCat.org, and gathered 2,918 responses. Phase three represented an analysis of two months of WorldCat.org transaction log data, consisting of over 15,000,000 sessions. Phase four was a lab based user study investigating and comparing the use of WorldCat.org with Amazon. Findings from each strand were integrated, and the key themes to emerge from the research are discussed. Different methods of classifying the WorldCat.org user population are presented, along with a taxonomy of work- and search-tasks. Key perspectives on the utility of a recommender system are considered, along with a reflection on how the information search behaviour exhibited by users interacting with recommendations while undertaking typical catalogue tasks can be interpreted. Based on the enriched perspective of the system, and the role of recommendation in the catalogue, a series of conceptual design specifications are presented for the development of a WorldCat.org recommender system

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

How do educators experience teaching with digital personalised learning:through the lens of Finnish and Flemish educators

Abstract. The use of educational technology has accelerated in primary and secondary education; platforms and tools are utilised on a weekly basis. The effect and impact of these technological implementations have not been met with the same speed. The work of educators is critical in incorporating those technologies, and in that regard, their significance is often under-researched. With a particular interest in primary education, I aim to include the voices of those standing in the classroom and implementing Digital Personalised Learning (DPL) tools such as the ViLLE platform and i-Learns’ online portal. Accordingly, this qualitative research study investigates (primary school) educators’ experiences with DPL using the ViLLE tool (Finland) and the i-Learn tool (Flanders/Belgium). This research aims to address the research question of “How do Educators Experience Teaching with Digital Personalised Learning?” by conducting semi-structured interviews with educators who have implemented DPL through the method of reflexive thematic analysis (RTA) following Braun and Clarke’s principles (2019). This study involves 12 educators (n=12), of which six are from the Belgian group and six from the Finnish one. With the constructionist epistemology of RTA, I explored the variety of experiences and the meaning given by these educators. The results found that support, autonomy, efficiency, effort and sentiment are important factors to consider when researching DPL efforts in these contexts. The most prevalent finding showcased the stress on educators exercising an active role within the classroom when using the DPL tool, in which description of guiding and facilitating students were prioritised. This study overall aims to provide several insights with important themes, such as the need for additional support, the role of efficiency and effort, and educators’ views on the extent of technology’s involvement in education. In addition, the findings provided insight into educators’ perceptions of technology’s role in education as either an aiding tool or regarded with an overtly technocentric view. It also showcases the need for future research. A discrepancy between the interpretation and the theoretical definition was showcased through participants’ emphasis on pupils’ autonomy and its importance which illustrated how the aspect of autonomy is significant to DPL from an educator’s perspective

Information retrieval from civil engineering repositories: the importance of context and granularity

Information about the design and construction of buildings can be structured in a particular way. This is especially correct given the increasing complexity of building product models and the emergence of building information models with project documents linked to them. In addition, engineers usually have distinct information needs. Research shows that engineers working with building information models place particular importance on the understanding of retrieved content before using it or applying it and that exploration of context is essential for this understanding. Both these factors (the nature of engineering content and the information needs of engineers) make general information retrieval techniques for computing relevance and visualizing search results less applicable in civil engineering information retrieval systems. This paper argues that granularity is a fundamental concept that needs to be considered when measuring relevance and visualizing search results in information retrieval systems for repositories of building design and construction content. It is hypothesized that the design of systems with careful regard for granularity would improve engineers’ relevance judgment behavior. To test this hypothesis, a prototype system, called CoMem-XML, was developed and evaluated in terms of the time needed for users to find relevant information, the accuracy of their relevance judgment, and their subjective satisfaction with the prototype. A user study was conducted in which test subjects were asked to complete tasks by using various forms of the prototype, to complete a satisfaction questionnaire, and to be interviewed. The findings show that users perform better and are more satisfied when the search result interface of the CoMem-XML system presents only relevant information in context. On the other hand, interfaces that present the retrieved information out of context (i.e., without highlighting its position in the parts hierarchy) are less effective for participants to judge relevance

Implicit feedback for interactive information retrieval

Searchers can find the construction of query statements for submission to Information Retrieval (IR) systems a problematic activity. These problems are confounded by uncertainty about the information they are searching for, or an unfamiliarity with the retrieval system being used or collection being searched. On the World Wide Web these problems are potentially more acute as searchers receive little or no training in how to search effectively. Relevance feedback (RF) techniques allow searchers to directly communicate what information is relevant and help them construct improved query statements. However, the techniques require explicit relevance assessments that intrude on searchers’ primary lines of activity and as such, searchers may be unwilling to provide this feedback. Implicit feedback systems are unobtrusive and make inferences of what is relevant based on searcher interaction. They gather information to better represent searcher needs whilst minimising the burden of explicitly reformulating queries or directly providing relevance information. In this thesis I investigate implicit feedback techniques for interactive information retrieval. The techniques proposed aim to increase the quality and quantity of searcher interaction and use this interaction to infer searcher interests. I develop search interfaces that use representations of the top-ranked retrieved documents such as sentences and summaries to encourage a deeper examination of search results and drive the information seeking process. Implicit feedback frameworks based on heuristic and probabilistic approaches are described. These frameworks use interaction to identify needs and estimate changes in these needs during a search. The evidence gathered is used to modify search queries and make new search decisions such as re-searching the document collection or restructuring already retrieved information. The term selection models from the frameworks and elsewhere are evaluated using a simulation-based evaluation methodology that allows different search scenarios to be modelled. Findings show that the probabilistic term selection model generated the most effective search queries and learned what was relevant in the shortest time. Different versions of an interface that implements the probabilistic framework are evaluated to test it with human subjects and investigate how much control they want over its decisions. The experiment involved 48 subjects with different skill levels and search experience. The results show that searchers are happy to delegate responsibility to RF systems for relevance assessment (through implicit feedback), but not more severe search decisions such as formulating queries or selecting retrieval strategies. Systems that help searchers make these decisions are preferred to those that act directly on their behalf or await searcher action