Behind the Wizard’s Curtain: Designing and Developing Intelligent Systems for use in Educational Contexts

This thesis concerns the design and development of intelligent systems for use in educational contexts. The work presented took part either side of the Covid-19 lockdowns of 2020 and 2021 which profoundly affected its direction. The earlier chapters, two to four, describe research conducted prior to 2021 and consider system design from the perspective of the system stakeholders and how interface choices may impact on stakeholders’ perceptions of a system’s capabilities. The latter part of the thesis, chapter six onwards, presents work conducted after the Covid-19 hiatus and is motivated largely by personal experience teaching remotely using video platforms such as MS Teams or Zoom. Stakeholders’ trust and acceptance of the outputs from intelligent systems are a common theme throughout the work. Chapter 5 reviews the literature between 2019 and 2022 spanning either side of the Covid period. Chapter 1 provides an introduction to the thesis outlining the approach taken, the research aims and objectives and the research contribution. Chapter 2 provides background to the main concepts presented and discusses the field of Child-Computer Interaction (CCI) with a focus on its development as a discrete research discipline distinct from Human-Computer Interaction (HCI). The chapter also highlights some of the challenges faced when conducting research with children including ethical considerations. It then presents an overview of Artificial Intelligence and some of its applications, followed by a brief history. It discusses Machine Learning based approaches that serve as support for the supervised learning implementations described in chapters 6, 7, and 8. Some of the building blocks of artificial neural networks, including feed-forward networks, backward propagation, and activation functions are also introduced. These ideas are further developed in Chapter 8 which describes an implementation that develops these concepts. The chapter concludes by looking at similar work currently being conducted in the field and notes that while other researchers are working on systems to automatically recognise engagement. The work described in the next chapters differs in its scope, intended target audience and methodology. Chapter 3 considers the deployment of an intelligent system in an educational context that monitors children’s behaviour during interaction with a computer or other digital technology and potentially makes an intervention if it identifies activity that may not be in the child’s best interest. A model is proposed to inform the design of such a system based on the relationship between trust and acceptance. The Trust Acceptance Mapping Model (TAMM) is presented as a tool to indicate the likely success of the intelligent system design. Chapter 4 explores how design choices regarding an IS’s interface may affect both acceptance of its outputs and perceptions of its capabilities. Two studies are presented both of which introduce children to a Poppy Humanoid Robot. The first study examines how anthropomorphising the system may impact children’s acceptance of its outputs. The children participating in the study perceived that a robot is able to learn while a computer is a rule based technology designed to perform well defined tasks. In the second study the researcher introduces the Poppy robot in either “humanised” or “robot” form. In humanised form, the robot is referred to as she or Poppy and the children are asked to suggest things Poppy can learn to do. In robotised form, the robot is referred to as it or the robot and the children are asked to identify tasks it can be programmed to complete. The study finds that when the robot was introduced in humanised form, the children were more likely to attribute actions requiring learning or intelligence to it. When the robot was introduced in robot form, the children are more likely to attribute physical activities to it. Chapter 5 presents a semi-systematic mapping review of the literature on HCI and CCI research related to AI. The terms HCI-AI and CCI-AI are used to describe the intersection between the disciplines. The AI taxonomy developed by AI Watch, the European Union’s service “to monitor the development, uptake and impact of Artificial Intelligence”, is used to classify and map the literature (Samoili et al., 2020). In reviewing the literature, three approaches are adopted. Natural Language Processing (NLP) is used to perform semantic labelling of the research. The papers are classified by the researcher using the AI domain and subdomains described in the taxonomy. Finally, the research methods employed to produce the research are classified using the same AI taxonomy. Chapter 6 presents PDLS, a peer observation approach to generate a labelled data set suitable for use in CCI research. The system is evaluated against the usability metrics of, effectiveness, efficiency, and satisfaction and is judged to be both efficient and satisfactory. Validation of its effectiveness is presented in Chapter 7. The CCI principle of Child Participation is central to the PDLS process, which generates labelled data in both a time and cost effective manner. Pupils were surveyed for their feelings on the accuracy of both their own and their peers’ judgments on engagement status after completing the task and expressed their confidence in both these aspects. It concludes by offering some thoughts that are intended to be helpful to other researchers who may wish to carry out similar studies and proposes the development of a data set that can be used as a resource for members of the CCI community who wish to undertake CCI research on emotion recognition or the application of computer vision to research with children. Chapter 7 uses two methods to evaluate the accuracy or effectiveness of the PDLS. The first method uses the iMotions software to retrospectively analyse the video data generated. The second method employs expert reviewers to watch the videos captured by the pupils in the PDLS study and record engagement statuses independently of the original decisions. Where there is an agreement between one or both of the reviewers and the observers original judgment, then the pupil observer’s label is considered accurate. Where there is disagreement, then this is reviewed by the author with the goal of establishing the reasons for the inconsistency. The chapter concludes by discussing the strengths and weaknesses of the system and makes recommendations for its development and improvement. Chapter 8 provides an overview of a Machine Learning based approach to implementing an engagement classifier for use with children in an educational context. The model described is a variant of a Recurrent Neural Network (RNN) called the Long Short-Term Memory (LSTM) Model and is selected for its ability to process sequences or cycles in the data. The output from the model is a binary classification which characterises the engagement level of the pupil completing the task as either engaged (1) or disengaged (0) and writes the classification to a video output. In presenting the model the author acknowledges its limitations and it does not represent a production model but rather demonstrates the feasibility of the approach. Although the implementation displays the engagement classification to the video, this is not intended as a preference over the other potential interfaces considered in Chapter 4. As such, the ML model which provides the engine for the implementation of this IS could support multiple embodiments of the system

Performance analysis for wireless G (IEEE 802.11G) and wireless N (IEEE 802.11N) in outdoor environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. The comparison consider on coverage area (mobility), throughput and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g

Performance Analysis For Wireless G (IEEE 802.11 G) And Wireless N (IEEE 802.11 N) In Outdoor Environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. the comparison consider on coverage area (mobility), through put and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g

Physical activity and exercise in dementia : an umbrella review of intervention and observational studies

Background: Dementia is a common condition in older people. Among the potential risk factors, increasing attention has been focused on sedentary behaviour. However, synthesizing literature exploring whether physical activity/exercise can affect health outcomes in people with dementia or with mild cognitive impairment (MCI) is still limited. Therefore, the aim of this umbrella review, promoted by the European Geriatric Medicine Society (EuGMS), is to understand the importance of physical activity/exercise for improving cognitive and non-cognitive outcomes in people with dementia/MCI. Methods: Umbrella review of systematic reviews (SR) (with or without meta-analyses) of randomized controlled trials (RCTs) and observational (prospective and case-control in people with MCI) studies based on a systematic literature search in several databases. The certainty of evidence of statistically significant outcomes attributable to physical activity/exercise interventions was evaluated using Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: Among 1,160 articles initially evaluated, 27 systematic reviews (4 without meta-analysis) for a total of 28,205 participants with dementia/MCI were included. No observational study on physical activity/exercise in MCI for preventing dementia was included. In SRs with MAs, physical activity/exercise was effective in improving global cognition in Alzheimer’s disease and in all types of dementia (very low/low certainty of evidence). Moreover, physical activity/ exercise significantly improved global cognition, attention, executive function, and memory in MCI, with a certainty of evidence varying from low to moderate. Finally, physical activity/exercise improved non-cognitive outcomes in people with dementia including falls and neuropsychiatric symptoms. SRs, without meta-analysis, corroborated these results. Conclusions: Supported by very low to moderate certainty of evidence, physical activity/exercise has a positive effect on several cognitive and non-cognitive outcomes in people with dementia and MCI, but RCTs, with low risk of bias/confounding, are still needed to confirm these findings

Association between number of medications and mortality in geriatric inpatients : a Danish nationwide register-based cohort study

Purpose: To explore the association between the number of medications and mortality in geriatric inpatients taking activities of daily living and comorbidities into account. Methods: A nationwide population-based cohort study was performed including all patients aged C65 years admitted to geriatric departments in Denmark during 2005-2014. The outcome of interest was mortality. Activities of daily living using Barthel-Index (BI) were measured at admission. National health registers were used to link data on an individual level extracting data on medications, and hospital diseases. Patients were followed to the end of study (31.12.2015), death, or emigration, which ever occurred first. Kaplan-Meier survival curves were used to estimate crude survival proportions. Univariable and multivariable analyses were performed using Cox regression. The multivariable analysis adjusted for age, marital status, period of hospital admission, BMI, and BI (model 1), and further adding either number of diseases (model 2) or Charlson comorbidity index (model 3). Results: We included 74603 patients (62.8% women), with a median age of 83 (interquartile range [IQR] 77-88) years. Patients used a median of 6 (IQR 4-9) medications. Increasing number of medications was associated with increased overall, 30-days, and 1-year mortality in all 3 multivariable models for both men and women. For each extra medication the mortality increased by 3% in women and 4% in men in the fully adjusted model. Conclusion: Increasing number of medications was associated with mortality in this nationwide cohort of geriatric inpatients. Our findings highlight the importance of polypharmacy in older patients with comorbidities

Deprescribing tool for STOPPFall (screening tool of older persons prescriptions in older adults with high fall risk) items

Background: Health care professionals are often reluctant to deprescribe fall-risk-increasing drugs (FRIDs). Lack of knowledge and skills form a significant barrier. To support clinicians in the management of FRIDs and to facilitate the deprescribing process, a deprescribing tool was developed by a European expert group for STOPPFall (Screening Tool of Older Persons Prescriptions in older adults with high fall risk) items. Methods: STOPPFall was created using an expert Delphi consensus process in 2019 and in 2020, 24 panellists from EuGMS SIG on Pharmacology and Task and Finish on FRIDs completed deprescribing tool questionnaire. To develop the questionnaire, a Medline literature search was performed. The panellists were asked to indicate for every medication class a possible need for stepwise withdrawal and strategy for withdrawal. They were asked in which situations withdrawal should be performed. Furthermore, panellists were requested to indicate those symptoms patients should be monitored for after deprescribing and a possible need for follow-ups. Results: Practical deprescribing guidance was developed for STOPPFall medication classes. For each medication class, a decision tree algorithm was developed including steps from medication review to symptom monitoring after medication withdrawal. Conclusion: STOPPFall was combined with a practical deprescribing tool designed to optimize medication review. This practical guide can help overcome current reluctance towards deprescribing in clinical practice by providing an up-to-date and straightforward source of expert knowledge

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.info:eu-repo/semantics/publishedVersio

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases