Teaching and learning in information retrieval

A literature review of pedagogical methods for teaching and learning information retrieval is presented. From the analysis of the literature a taxonomy was built and it is used to structure the paper. Information Retrieval (IR) is presented from different points of view: technical levels, educational goals, teaching and learning methods, assessment and curricula. The review is organized around two levels of abstraction which form a taxonomy that deals with the different aspects of pedagogy as applied to information retrieval. The first level looks at the technical level of delivering information retrieval concepts, and at the educational goals as articulated by the two main subject domains where IR is delivered: computer science (CS) and library and information science (LIS). The second level focuses on pedagogical issues, such as teaching and learning methods, delivery modes (classroom, online or e-learning), use of IR systems for teaching, assessment and feedback, and curricula design. The survey, and its bibliography, provides an overview of the pedagogical research carried out in the field of IR. It also provides a guide for educators on approaches that can be applied to improving the student learning experiences

Credibility: A multidisciplinary framework

No Abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/61241/1/1440410114_ftp.pd

The use of implicit evidence for relevance feedback in web retrieval

In this paper we report on the application of two contrasting types of relevance feedback for web retrieval. We compare two systems; one using explicit relevance feedback (where searchers explicitly have to mark documents relevant) and one using implicit relevance feedback (where the system endeavours to estimate relevance by mining the searcher's interaction). The feedback is used to update the display according to the user's interaction. Our research focuses on the degree to which implicit evidence of document relevance can be substituted for explicit evidence. We examine the two variations in terms of both user opinion and search effectiveness

Evaluating the retrieval effectiveness of Web search engines using a representative query sample

Search engine retrieval effectiveness studies are usually small-scale, using only limited query samples. Furthermore, queries are selected by the researchers. We address these issues by taking a random representative sample of 1,000 informational and 1,000 navigational queries from a major German search engine and comparing Google's and Bing's results based on this sample. Jurors were found through crowdsourcing, data was collected using specialised software, the Relevance Assessment Tool (RAT). We found that while Google outperforms Bing in both query types, the difference in the performance for informational queries was rather low. However, for navigational queries, Google found the correct answer in 95.3 per cent of cases whereas Bing only found the correct answer 76.6 per cent of the time. We conclude that search engine performance on navigational queries is of great importance, as users in this case can clearly identify queries that have returned correct results. So, performance on this query type may contribute to explaining user satisfaction with search engines

From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Does it matter which search engine is used? A user study using post-task relevance judgments

The objective of this research was to find out how the two search engines Google and Bing perform when users work freely on pre-defined tasks, and judge the relevance of the results immediately after finishing their search session. In a user study, 64 participants conducted two search tasks each, and then judged the results on the following: (1) The quality of the results they selected in their search sessions, (2) The quality of the results they were presented with in their search sessions (but which they did not click on), (3) The quality of the results from the competing search engine for their queries (which they did not see in their search session). We found that users heavily relied on Google, that Google produced more relevant results than Bing, that users were well able to select relevant results from the results lists, and that users judged the relevance of results lower when they regarded a task as difficult and did not find the correct information

Digital Library Evaluation: Toward an Evolution of Concepts

published or submitted for publicatio

Using new assessment tools during and post-COVID-19

This work tackles the need to evaluate and identify fresh assessment techniques utilized in LIS education during and after the COVID-19 epidemic. It investigates the impact of digital media, feedback, formative assessments, and concerns such as cheating and authenticity, providing critical insights for future assessment practises in the post-pandemic period. Accordingly, there is a pressing need to employ new assessment tools post-pandemic to adapt to online and hybrid learning challenges. This qualitative study investigates complex social phenomena in higher education assessments by exploring behaviours, preferences, beliefs, customs, attitudes, viewpoints, and experiences. Twelve LIS instructors, 6 teaching and learning administrators, and 20 LIS students from South Africa and Nigeria were chosen using convenience sampling. Key informant interviews were conducted, with constructivist learning orientation-driven questions examining new assessment technologies, the role of digital media in student assessment, authenticity concerns in e-assessment, feedback and formative assessments. The research concludes that incorporating Computer-Based Learning (CLT) in e-assessments for LIS education enhances students’ knowledge construction and accessibility. Digital examinations offer benefits like instant feedback and personalized learning experiences, leading to improved problem-solving skills and decision-making. Future research should focus on larger, diverse samples and longitudinal approaches to evaluate intervention effectiveness and sustainability