Effect of Tuned Parameters on a LSA MCQ Answering Model

This paper presents the current state of a work in progress, whose objective is to better understand the effects of factors that significantly influence the performance of Latent Semantic Analysis (LSA). A difficult task, which consists in answering (French) biology Multiple Choice Questions, is used to test the semantic properties of the truncated singular space and to study the relative influence of main parameters. A dedicated software has been designed to fine tune the LSA semantic space for the Multiple Choice Questions task. With optimal parameters, the performances of our simple model are quite surprisingly equal or superior to those of 7th and 8th grades students. This indicates that semantic spaces were quite good despite their low dimensions and the small sizes of training data sets. Besides, we present an original entropy global weighting of answers' terms of each question of the Multiple Choice Questions which was necessary to achieve the model's success.Comment: 9 page

Algorithms for assessing the quality and difficulty of multiple choice exam questions

Multiple Choice Questions (MCQs) have long been the backbone of standardized testing in academia and industry. Correspondingly, there is a constant need for the authors of MCQs to write and refine new questions for new versions of standardized tests as well as to support measuring performance in the emerging massive open online courses, (MOOCs). Research that explores what makes a question difficult, or what questions distinguish higher-performing students from lower-performing students can aid in the creation of the next generation of teaching and evaluation tools. In the automated MCQ answering component of this thesis, algorithms query for definitions of scientific terms, process the returned web results, and compare the returned definitions to the original definition in the MCQ. This automated method for answering questions is then augmented with a model, based on human performance data from crowdsourced question sets, for analysis of question difficulty as well as the discrimination power of the non-answer alternatives. The crowdsourced question sets come from PeerWise, an open source online college-level question authoring and answering environment. The goal of this research is to create an automated method to both answer and assesses the difficulty of multiple choice inverse definition questions in the domain of introductory biology. The results of this work suggest that human-authored question banks provide useful data for building gold standard human performance models. The methodology for building these performance models has value in other domains that test the difficulty of questions and the quality of the exam takers

Sentence Similarity Analysis with Applications in Automatic Short Answer Grading

In this dissertation, I explore unsupervised techniques for the task of automatic short answer grading. I compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating automatic feedback from the student answers. I continue to combine graph alignment features with lexical semantic similarity measures and employ machine learning techniques to show that grade assignment error can be reduced compared to a system that considers only lexical semantic measures of similarity. I also detail a preliminary attempt to align the dependency graphs of student and instructor answers in order to utilize a structural component that is necessary to simulate human-level grading of student answers. I further explore the utility of these techniques to several related tasks in natural language processing including the detection of text similarity, paraphrase, and textual entailment

Comprehension based adaptive learning systems

Conversational Intelligent Tutoring Systems aim to mimic the adaptive behaviour of human tutors by delivering tutorial content as part of a dynamic exchange of information conducted using natural language. Deciding when it is beneficial to intervene in a student’s learning process is an important skill for tutoring. Human tutors use prior knowledge about the student, discourse content and learner non-verbal behaviour to choose when intervention will help learners overcome impasse. Experienced human tutors adapt discourse and pedagogy based on recognition of comprehension and non-comprehension indicative learner behaviour. In this research non-verbal behaviour is explored as a method of computationally analysing reading comprehension so as to equip an intelligent conversational agent with the human-like ability to estimate comprehension from non-verbal behaviour as a decision making trigger for feedback, prompts or hints. This thesis presents research that combines a conversational intelligent tutoring system (CITS) with near real-time comprehension classification based on modelling of e-learner non-verbal behaviour to estimate learner comprehension during on-screen conversational tutoring and to use comprehension classifications as a trigger for intervening with hints, prompts or feedback for the learner. To improve the effectiveness of tuition in e-learning, this research aims to design, develop and demonstrate novel computational methods for modelling e-learner comprehension of on-screen information in near real-time and for adapting CITS tutorial discourse and pedagogy in response to perception of comprehension indicative behaviour. The contribution of this research is to detail the motivation for, design of, and evaluation of a system which has the human-like ability to introduce micro-adaptive feedback into tutorial discourse in response to automatic perception of e-learner reading comprehension. This research evaluates empirically whether e-learner non-verbal behaviour can be modelled to classify comprehension in near real-time and presents a near real-time comprehension classification system which achieves normalised comprehension classification accuracy of 75%. Understanding e-learner comprehension creates exciting opportunities for advanced personalisation of materials, discourse, challenge and the digital environment itself. The research suggests a benefit is gained from comprehension based adaptation in conversational intelligent tutoring systems, with a controlled trial of a comprehension based adaptive CITS called Hendrix 2.0 showing increases in tutorial assessment scores of up to 17% when comprehension based discourse adaptation is deployed to scaffold the learning experience

Adaptive computer assisted assessment of free-text students' answers: an approach to automatically generate students' conceptual models

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, mayo de 200

An investigation into computer and network curricula

This thesis consists of a series of internationally published, peer reviewed, journal and conference research papers that analyse the educational and training needs of undergraduate Information Technology (IT) students within the area of Computer and Network Technology (CNT) Education. Research by Maj et al has found that accredited computing science curricula can fail to meet the expectations of employers in the field of CNT: “It was found that none of these students could perform first line maintenance on a Personal Computer (PC) to a professional standard with due regard to safety, both to themselves and the equipment. Neither could they install communication cards, cables and network operating system or manage a population of networked PCs to an acceptable commercial standard without further extensive training. It is noteworthy that none of the students interviewed had ever opened a PC. It is significant that all those interviewed for this study had successfully completed all the units on computer architecture and communication engineering (Maj, Robbins, Shaw, & Duley, 1998). The students\u27 curricula at that time lacked units in which they gained hands-on experience in modern PC hardware or networking skills. This was despite the fact that their computing science course was level one accredited, the highest accreditation level offered by the Australian Computer Society (ACS). The results of the initial survey in Western Australia led to the introduction of two new units within the Computing Science Degree at Edith Cowan University (ECU), Computer Installation & Maintenance (CIM) and Network Installation & Maintenance (NIM) (Maj, Fetherston, Charlesworth, & Robbins, 1998). Uniquely within an Australian university context these new syllabi require students to work on real equipment. Such experience excludes digital circuit investigation, which is still a recommended approach by the Association for Computing Machinery (ACM) for computer architecture units (ACM, 2001, p.97). Instead, the CIM unit employs a top-down approach based initially upon students\u27 everyday experiences, which is more in accordance with constructivist educational theory and practice. These papers propose an alternate model of IT education that helps to accommodate the educational and vocational needs of IT students in the context of continual rapid changes and developments in technology. The ACM have recognised the need for variation noting that: There are many effective ways to organize a curriculum even for a particular set of goals and objectives (Tucker et al., 1991, p.70). A possible major contribution to new knowledge of these papers relates to how high level abstract bandwidth (B-Node) models may contribute to the understanding of why and how computer and networking technology systems have developed over time. Because these models are de-coupled from the underlying technology, which is subject to rapid change, these models may help to future-proof student knowledge and understanding of the ongoing and future development of computer and networking systems. The de-coupling is achieved through abstraction based upon bandwidth or throughput rather than the specific implementation of the underlying technologies. One of the underlying problems is that computing systems tend to change faster than the ability of most educational institutions to respond. Abstraction and the use of B-Node models could help educational models to more quickly respond to changes in the field, and can also help to introduce an element of future-proofing in the education of IT students. The importance of abstraction has been noted by the ACM who state that: Levels of Abstraction: the nature and use of abstraction in computing; the use of abstraction in managing complexity, structuring systems, hiding details, and capturing recurring patterns; the ability to represent an entity or system by abstractions having different levels of detail and specificity (ACM, 1991b). Bloom et al note the importance of abstraction, listing under a heading of: “Knowledge of the universals and abstractions in a field” the objective: Knowledge of the major schemes and patterns by which phenomena and ideas arc organized. These are large structures, theories, and generalizations which dominate a subject or field or problems. These are the highest levels of abstraction and complexity\u27\u27 (Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956, p. 203). Abstractions can be applied to computer and networking technology to help provide students with common fundamental concepts regardless of the particular underlying technological implementation to help avoid the rapid redundancy of a detailed knowledge of modem computer and networking technology implementation and hands-on skills acquisition. Again the ACM note that: “Enduring computing concepts include ideas that transcend any specific vendor, package or skill set... While skills are fleeting, fundamental concepts are enduring and provide long lasting benefits to students, critically important in a rapidly changing discipline (ACM, 2001, p.70) These abstractions can also be reinforced by experiential learning to commercial practices. In this context, the other possibly major contribution of new knowledge provided by this thesis is an efficient, scalable and flexible model for assessing hands-on skills and understanding of IT students. This is a form of Competency-Based Assessment (CBA), which has been successfully tested as part of this research and subsequently implemented at ECU. This is the first time within this field that this specific type of research has been undertaken within the university sector within Australia. Hands-on experience and understanding can become outdated hence the need for future proofing provided via B-Nodes models. The three major research questions of this study are: •Is it possible to develop a new, high level abstraction model for use in CNT education? •Is it possible to have CNT curricula that are more directly relevant to both student and employer expectations without suffering from rapid obsolescence? •Can WI effective, efficient and meaningful assessment be undertaken to test students\u27 hands-on skills and understandings? The ACM Special Interest Group on Data Communication (SJGCOMM) workshop report on Computer Networking, Curriculum Designs and Educational Challenges, note a list of teaching approaches: ... the more \u27hands-on\u27 laboratory approach versus the more traditional in-class lecture-based approach; the bottom-up approach towards subject matter verus the top-down approach (Kurose, Leibeherr, Ostermann, & Ott-Boisseau, 2002, para 1). Bandwidth considerations are approached from the PC hardware level and at each of the seven layers of the International Standards Organisation (ISO) Open Systems Interconnection (OSI) reference model. It is believed that this research is of significance to computing education. However, further research is needed

Using technology to enhance learning, progression and achievement in higher education

The efficiency of the use of technology in higher education teaching and learning has seen limited research which has been mainly theoretical in nature. The research aims to identify the effects of using technology to enhance learning, progression and achievement in Higher Education. The literature review identified a gap, and this study is situated here to provide a proposed solution to the identified problem. The approach taken is iterative, as it seeks to find a solution to a perceived problem. The research reviews the effect of Technology Enhanced Learning (TEL) on student case studies and establishes whether technology enhancement can be personalised for learners. The research comprises of three individual studies which form the research design and the construction of the pedagogical model is the result of three studies data. The first study investigates the strategic element of TEL implementation from a programme perspective. The second study gains the student voice on the implementation of TEL. The final study measures the effectiveness of TEL implementation at a module level with a focus on personalisation of learning resources. The methodology adopted is viewed through a pragmatist lens, which enables relevant research instruments to be used to find the solution through the use of mixed methods. The results from this research are used to produce a pedagogical model for the implementation of technology into teaching and learning for modules in HE programmes. The model production process identifies the impact of the major findings from the three studies and to assess the effectiveness of the proposed model before testing it statistically for acceptance. The proposed pedagogical model adds to the established research and gives guidance on the implementation of technology in taught modules in a strategic and consistent manner, offering a level of self-personalisation to support learning in the most effective way. The model and accompanying guidance add knowledge to the area, build on published research and will develop practice. The research will contribute knowledge to the area through a new way of looking at TEL pedagogy, manifested in the proposed implementation model

Technology and Testing

From early answer sheets filled in with number 2 pencils, to tests administered by mainframe computers, to assessments wholly constructed by computers, it is clear that technology is changing the field of educational and psychological measurement. The numerous and rapid advances have immediate impact on test creators, assessment professionals, and those who implement and analyze assessments. This comprehensive new volume brings together leading experts on the issues posed by technological applications in testing, with chapters on game-based assessment, testing with simulations, video assessment, computerized test development, large-scale test delivery, model choice, validity, and error issues. Including an overview of existing literature and ground-breaking research, each chapter considers the technological, practical, and ethical considerations of this rapidly-changing area. Ideal for researchers and professionals in testing and assessment, Technology and Testing provides a critical and in-depth look at one of the most pressing topics in educational testing today

Attention Restraint, Working Memory Capacity, and Mind Wandering: Do Emotional Valence or Intentionality Matter?

Attention restraint appears to mediate the relationship between working memory capacity (WMC) and mind wandering (Kane et al., 2016). Prior work has identifed two dimensions of mind wandering—emotional valence and intentionality. However, less is known about how WMC and attention restraint correlate with these dimensions. Te current study examined the relationship between WMC, attention restraint, and mind wandering by emotional valence and intentionality. A confrmatory factor analysis demonstrated that WMC and attention restraint were strongly correlated, but only attention restraint was related to overall mind wandering, consistent with prior fndings. However, when examining the emotional valence of mind wandering, attention restraint and WMC were related to negatively and positively valenced, but not neutral, mind wandering. Attention restraint was also related to intentional but not unintentional mind wandering. Tese results suggest that WMC and attention restraint predict some, but not all, types of mind wandering