A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM

We present Korbit, a large-scale, open-domain, mixed-interface, dialogue-based intelligent tutoring system (ITS). Korbit uses machine learning, natural language processing and reinforcement learning to provide interactive, personalized learning online. Korbit has been designed to easily scale to thousands of subjects, by automating, standardizing and simplifying the content creation process. Unlike other ITS, a teacher can develop new learning modules for Korbit in a matter of hours. To facilitate learning across a widerange of STEM subjects, Korbit uses a mixed-interface, which includes videos, interactive dialogue-based exercises, question-answering, conceptual diagrams, mathematical exercises and gamification elements. Korbit has been built to scale to millions of students, by utilizing a state-of-the-art cloud-based micro-service architecture. Korbit launched its first course in 2019 on machine learning, and since then over 7,000 students have enrolled. Although Korbit was designed to be open-domain and highly scalable, A/B testing experiments with real-world students demonstrate that both student learning outcomes and student motivation are substantially improved compared to typical online courses

The role of Comprehension in Requirements and Implications for Use Case Descriptions

Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements. Therefore, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Hence, the paper examines guidelines which have been proposed, in this case for use case descriptions, and the extent to which they agree with discourse process theory; before suggesting refinements to the guidelines which attempt to utilise lessons learned from our richer understanding of the underlying discourse process theory. For example, we suggest subtly different sets of writing guidelines for the different tasks of requirements, specification and design

Interaction analysis in online maths human tutoring: The case of third space learning

This 'industry' paper reports on the combined effort of researchers and industrial designers and developers to ground the automatic quality assurance of online maths human-to-human tutoring on best practices. We focus on the first step towards this goal. Our aim is to understand the largely under-researched field of online tutoring, to identify success factors in this context and to model best practice in online teaching. We report our research into best practice in online maths teaching and describe and discuss our design and evaluation iterations towards annotation software that can mark up human-to-human online teaching interactions with successful teaching interaction signifiers

‘Question Moments’: A Rolling Programme of Question Opportunities in Classroom Science

This article has been made available through the Brunel Open Access Publishing Fund.This naturalistic study integrates specific 'question moments' into lesson plans to increase pupils' classroom interactions. A range of teaching tools has explored students' ideas through opportunities to ask and write questions. Their oral and written outcomes provide data on individual and group misunderstandings. Changes to the schedule of lessons were introduced to discuss these questions and solve disparities. Flexible lesson planning over fourteen lessons across a four-week period of highschool chemistry accommodated students' contributions and increased student participation, promoted inquiring and individualised teaching, with each teaching strategy feeding forward into the next

ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis

Analyzing the readability of articles has been an important sociolinguistic task. Addressing this task is necessary to the automatic recommendation of appropriate articles to readers with different comprehension abilities, and it further benefits education systems, web information systems, and digital libraries. Current methods for assessing readability employ empirical measures or statistical learning techniques that are limited by their ability to characterize complex patterns such as article structures and semantic meanings of sentences. In this paper, we propose a new and comprehensive framework which uses a hierarchical self-attention model to analyze document readability. In this model, measurements of sentence-level difficulty are captured along with the semantic meanings of each sentence. Additionally, the sentence-level features are incorporated to characterize the overall readability of an article with consideration of article structures. We evaluate our proposed approach on three widely-used benchmark datasets against several strong baseline approaches. Experimental results show that our proposed method achieves the state-of-the-art performance on estimating the readability for various web articles and literature.Comment: ECIR 202

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

STyLE-OLM (Dimitrova 2003 International Journal of Artificial Intelligence in Education, 13, 35–78) presented a framework for interactive open learner modelling which entails the development of the means by which learners can inspect, discuss and alter the learner model that has been jointly constructed by themselves and the system. This paper outlines the STyLE-OLM framework and reflects on the key challenges it addressed: (a) the design of an appropriate communication medium; this was addressed by proposing a structured language using diagrammatic presentations of conceptual graphs; (b) the management of the interaction with the learner; this was addressed by designing a framework for interactive open learner modelling dialogue utilising dialogue games; (c) the accommodation of different beliefs about the learner’s domain model; this was addressed with a mechanism for maintaining different views about the learner beliefs which adapted belief modal logic operators; and (d) the assessment of any resulting improvements in learner model accuracy and learner reflection; this was addressed in a user study with an instantiation of STyLE-OLM for diagnosing a learner’s knowledge of finance concept, as part of a larger project that developed an intelligent system to assist with learning domain terminology in a foreign language. Reviewing follow on work, we refer to projects by the authors’ students and colleagues leading to further extension and adoption of STyLE-OLM, as well as relevant approaches in open learner modelling which have cited the STyLE-OLM framework. The paper points at outstanding research challenges and outlines future a research direction to extend interactive open learner modelling towards mentor-like intelligent learning systems

The Postpartum Specific Anxiety Scale: development and preliminary validation

Perinatal symptoms of anxiety are increasingly recognised due to their high prevalence and impact. Studies using pregnancy-specific anxiety measures have found that they may predict perinatal outcomes more effectively than general measures. However, no such measure exists to assess anxieties specific to the postpartum. This study aimed to develop and validate a measure (Postpartum Specific Anxiety Scale; PSAS) that accurately represents the specific anxieties faced by postpartum women, using a four-stage methodology: (1) 51 items were generated from interviews conducted with a group of 19 postpartum women at two time points, (2) the scale was reviewed and refined by a diverse expert panel, (3) an online pilot study (n = 146) was conducted to assess comprehensibility and acceptability and (4) an online sample of 1282 mothers of infants up to 6 months old completed the PSAS against a battery of convergent measures. A subsample (n = 262) repeated the PSAS 2 weeks later. The PSAS possessed good face and content validity and was comprehensible and acceptable to postpartum women. PSAS scores were significantly correlated with other measures indicating good convergent validity. Principal component analyses (PCA) revealed a simple four-factor structure. Reliability of the overall scale and individual PSAS factors proved to be good to excellent. A preliminary receiver operating characteristic (ROC) analysis also suggested that the PSAS may be a useful screening tool. The psychometric evidence suggests that the PSAS is an acceptable, valid, and reliable research tool to assess anxieties, which are specific to the postpartum period. Next steps in the iterative validation process are considered for both research and screening purposes

ReaderBench Learns Dutch: Building a Comprehensive Automated Essay Scoring System for Dutch Language

Automated Essay Scoring has gained a wider applicability and usage with the integration of advanced Natural Language Processing techniques which enabled in-depth analyses of discourse in order capture the specificities of written texts. In this paper, we introduce a novel Automatic Essay Scoring method for Dutch language, built within the Readerbench framework, which encompasses a wide range of textual complexity indices, as well as an automated segmentation approach. Our method was evaluated on a corpus of 173 technical reports automatically split into sections and subsections, thus forming a hierarchical structure on which textual complexity indices were subsequently applied. The stepwise regression model explained 30.5% of the variance in students’ scores, while a Discriminant Function Analysis predicted with substantial accuracy (75.1%) whether they are high or low performance students.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains

Experiencing neutropenia: Quality of life interviews with adult cancer patients

BACKGROUND: Neutropenia is a common toxicity in chemotherapy but detailed information about how neutropenia is associated with changes in patients' quality of life is not readily available. This prospective study interviewed patients with grade 4 neutropenia to provide qualitative information on patients' experience of developing and coping with grade 4 neutropenia during a cycle of chemotherapy. METHODS: A sample of 34 patients who developed grade 4 neutropenia during the first cycle of chemotherapy completed a total of 100 structured clinical interviews. Interviews were transcribed, and 2 raters inductively developed 5 broad categories comprising 80 specific complaint domains nominated by patients. Thirty-five patient-nominated problems were mentioned in 5% or more of the interviews. RESULTS: Fatigue was the most common physical symptom. Interference in daily routine, negative self-evaluation, negative emotion, and social isolation were other common complaints associated with neutropenia. CONCLUSION: Neutropenia is associated with a number of negative experiences among cancer patients undergoing chemotherapy, and these negative experiences have an adverse effect on the patient's quality of life. Oncology nurses can play a key role in helping patients manage adverse effects to maintain their quality of life