User Skills Research Articles

An Assessment of Librarians ICT Skills in Federal University of Technology Library, Minna, Nigeria

31 https://doi.org/10.70118/ijkd.0202405010.4 © 2024 The Authors, Samuel Ogbemudia Library. ISSN: Print 2714-4356 / Online 2714-4364 Published by Samuel Ogbemudia Library, University of Abuja, Nigeria An Assessment of Librarians ICT Skills in Federal University of Technology Library, Minna, Nigeria Mohammed Saba Adamu1* and Ladan Dogara1 1University Library, Federal University of Technology Minna, Niger State, Nigeria. *mohd.adamu@futminna.edu.ng Abstract This study examined ICT skills of librarians in Federal University of Technology Library, Minna, Niger State, Nigeria. The study adopted descriptive survey research design. Two research questions guided the study. The study population comprised twenty-six (26) librarians working in Federal University of Technology Library, Minna, Nigeria. A structured questionnaire was the instrument for data collection. Data were analysed using frequency counts, percentage and mean as a measure of central tendency with criterion mean of 3.0 benchmark. Findings revealed that the level of possession of ICT skills of the librarians is high in the areas of basic operation of ICT hardware skills, Internet usage skills, online research skills, online communication, and collaboration. and social/academic networking sites management and email skills and low in the area of document creation and retrieval skills. Conferences, workshops, self-learning, peer coaching, mentoring and among others were the avenues of ICT skills acquisition of the librarians. Based on the findings, the study concluded that librarians need to improve on the aspects of low possession of ICT skills. The study recommended that librarians should sustain and improve upon their possession of ICT skills through periodic training and re-training.

Model of Flipped Classroom Environment for Mastery Learning Approach Using the “ZOOMRBT App”

In the digital era that encourages innovation in educational technology, it is crucial to incorporate the use of technology into pedagogy. Since the inception of hybrid learning and other approaches that involve students and instructors in educational activities, the learning environment has undergone significant changes. By utilizing instructional resources such as textbooks and videos, it has become feasible to engage with students beyond the confines of the classroom and during evening hours. Research conducted on students in grades 8 and 9 in Ontario, Canada, revealed that due to their limited spare time, they opted to study and complete their homework after school. Moreover, they exhibited a clear prioritization of their depth of subject knowledge over other factors. The study aimed to adapt the existing learning environment to establish a new environment conducive to mastery learning. It involved fifteen student participants, including an expert teacher in the flipped classroom teaching method. The study employed qualitative techniques such as focus groups, document analysis, expert agreement percentages, and innovative flipping of the classroom. The study resulted in the identification of five thematic analyses: learning flexibility, application skills, usage of application skills, mastery assessment, and the human touch. Collectively, these qualitative findings provide compelling evidence that the research participants actively engage with various aspects of the flipped learning environment, as outlined by the aforementioned themes. The participants in the case study acted as both fresh and established elements within the flipped learning environment.

Big Data as a reform opportunity for public sector and real economy: The case of Greece

Background The recent economic recession has hit Greece with economic, political, and social repercussions. Structural reforms in the real economy and public sector are considered to be of paramount importance for introducing a new consumption and production paradigm to achieve sustainable economic growth. Methods The present paper aims to highlight Big Data and the Internet of Things as part of the 4th Industrial Revolution as a potential enabler for the necessary leap in the 21st century for the Greek public sector on the theoretical basis of the Unified Growth Theory and the Washington Doctrine. In the present paper, an evaluation of the Greek public sector is attempted by using two different indices, the Digital Maturity Index of the Hellenic Federation of Enterprises (SEV), and the Digital Economy and Society Index (DESI) of the EU. Results Findings strongly indicate that the introduction of digital skills in the educational system along with vocational training of older groups regarding the use of digital public services is an important factor for digital services implementation in the case of Greece. Moreover, the findings also underlie that demand for digital public services is not merely a matter of economic power. Other causes that lie in cultural, geographical, and behavioural habits should also be considered. Conclusions Greece is not in the pole position regarding Big Data implementation. High-speed broadband, both fast and ultrafast, lacks widespread availability, while prices remain relatively high compared to other European countries. Internet user skills and advanced IT skills remain mostly misused in the private and the public sector, while business digitization, e-commerce, e-Government, and e-health remain relatively low.

Abbreviated Dialectical Behavior Therapy Virtual Skills Group for Caregivers of Adolescents: An Exploratory Study of Service User and Clinical Outcomes.

Prior work emphasizes involving caregivers in youth mental health services. To support youth with emotion dysregulation, dialectical behavior therapy for adolescents (DBT-A) includes a multi-family skills group, wherein adolescents and caregivers learn skills together. However, limited work has examined the impact of caregiver involvement within DBT-A. The current study examines outcomes of two caregiver-only DBT-A skills groups adapted for abbreviated telehealth delivery. We report on caregivers' (N = 11, 100% mothers, 55% Hispanic) service user outcomes (e.g. self-efficacy at skill usage, group cohesion, therapeutic alliance) and clinical outcomes (i.e. their own emotion functioning, criticism, responses to their adolescent's negative emotions). Results indicate caregiver-only groups were feasible and acceptable, and suggest preliminary efficacy, including improvements in caregiver emotion functioning, distress during interactions with their adolescents, and adolescent-reported criticism. Caregivers also reported reductions in unsupportive responses with their adolescents. Overall, while we caution interpretation due to a small sample size, findings support the preliminary feasibility and efficacy of modifying caregiver participation in DBT-A to be less time-consuming and administered via telehealth.

The role of youth in overcoming the digital divide between generational groups

One of the main resources of modern society is information and digital technologies for its processing. Access to information, digital products and services helps reduce barriers in an individual’s interaction with the state, organizations, and other individuals, and provides opportunities for personal development and active participation in solving social issues. At the same time, the uneven distribution of information infrastructure, differences in the skills of users when working with digital products, as well as varying degrees of motivation of individuals to work on the Internet form digital divide. Based on the key concepts of digital divide, in September 2022 - April 2023, the authors conducted a sociological study in which residents of the Sverdlovsk region took part. Based on the results of the study, the authors come to the conclusion that age is one of the key factors in the reproduction of digital divide, and therefore digital divide between generations of modern Russian society is relevant. The results of the study demonstrated the leading role of youth in bridging the digital divide between generational groups, since young Internet users have more developed digital skills, and representatives of the older generation are ready to acquire these skills when interacting with youth.

Monitoring Educational Intervention Programs for Children and Young People with Disabilities through a Web Application

Early care professionals have to use instruments for assessing functional skills in children susceptible to early intervention that apply records and produce developmental profiles and personalized intervention proposals. The aims of the study were (1) to analyze the development of functional skills in users with an age range of 48–252 months attending school in a therapeutic intervention center for people with motor impairments; and (2) to analyze the development of functional skills in users with different impairments and ages ranging from 7 to 162 months participating in an early outpatient care program. Study 1 applied a sample of 50 users aged between 48 and 252 months all with motor disabilities and Study 2 included a sample of 71 users aged between 7 and 162 months with different disabilities. Factorial and descriptive–correlational designs were applied in both studies. The Student’s t-test for dependent samples, supervised machine learning techniques (linear regression analysis and logarithmic regression analysis), unsupervised machine learning techniques (k-means), ANOVA, and cross-tabulations were used as contrast tests. In Study 1, no significant changes were found in the development of users’ functional skills, except for a decrease in maladaptive behaviors. Likewise, the chronological age variable did not seem to be a determining factor in the results. In Study 2, significant differences were found in the development of all functional skills between the three measurement time points (initial–intermediate–final). In this group, the type of impairment explained 29% and chronological age 40% of the variance in functional development at the final measurement. This study found that intervention before four years old in outpatient mode produced better results in the acquisition of functional skills, with better results in users affected by rare diseases or communication and language delay at ages 49–60 months.

Analysis of The Influence of Enterprise Resources Planning Adoption and Information Technology Applications on Quality of Accounting Report

This study aims to ascertain how user skills, information technology utilization, and enterprise resource planning (ERP) adoption affect accounting report quality. Causal study methodology is employed in this work. The method for gathering data was a questionnaire. The study's respondents are employees who have used accounting information systems. Convenience sampling, or non-probability sampling, was used to choose the sample for this study. Multiple linear regressions are employed in this study. According to the research findings, the use of enterprise resource planning, information technology, and user knowledge together had a favorable and significant effect on the quality of accounting information. The quality of accounting information can be enhanced by ERP adoption when backed by top management commitment and support, ease of system integration, system capacity to meet needs, vendor training, and solutions that satisfy needs. The quality of accounting information is positively impacted by IT, which is supported by a solid infrastructure, including functionally matched computers, computer networks, internet access, effective accounting procedures, software-assisted data processing, information system output, and infrastructure upkeep. Furthermore, the quality of accounting information can be enhanced by solid user knowledge, reinforced by education, training, and user experience. When managing accounting information systems, businesses must consider these criteria to guarantee that the data generated is reliable, accurate, timely, comprehensive, and verifiable. Thus, companies can make better decisions based on accurate and relevant information.

Measuring and monitoring skill learning in closed-loop myoelectric hand prostheses using speed-accuracy tradeoffs

Objective. Closed-loop myoelectric prostheses, which combine supplementary sensory feedback and electromyography (EMG) based control, hold the potential to narrow the divide between natural and bionic hands. The use of these devices, however, requires dedicated training. Therefore, it is crucial to develop methods that quantify how users acquire skilled control over their prostheses to effectively monitor skill progression and inform the development of interfaces that optimize this process. Approach. Building on theories of skill learning in human motor control, we measured speed-accuracy tradeoff functions (SAFs) to comprehensively characterize learning-induced changes in skill—as opposed to merely tracking changes in task success across training—facilitated by a closed-loop interface that combined proportional control and EMG feedback. Sixteen healthy participants and one individual with a transradial limb loss participated in a three-day experiment where they were instructed to perform the box-and-blocks task using a timed force-matching paradigm at four specified speeds to reach two target force levels, such that the SAF could be determined. Main results. We found that the participants’ accuracy increased in a similar way across all speeds we tested. Consequently, the shape of the SAF remained similar across days, at both force levels. Further, we observed that EMG feedback enabled participants to improve their motor execution in terms of reduced trial-by-trial variability, a hallmark of skilled behavior. We then fit a power law model of the SAF, and demonstrated how the model parameters could be used to identify and monitor changes in skill. Significance. We comprehensively characterized how an EMG feedback interface enabled skill acquisition, both at the level of task performance and movement execution. More generally, we believe that the proposed methods are effective for measuring and monitoring user skill progression in closed-loop prosthesis control.

Determining the factors affecting the ICT use of Turkish students attending PISA-2018: Multilevel profile analysis approach

This study aims to classify student profiles based on the type and frequency of Information and Communication Technologies (ICT) usage. Each profile exhibits homogeneous characteristics and heterogeneous characteristics compared to other groups. Additionally, the study investigates whether covariates at the school and student levels create differences in these profiles. For this purpose, a mixed-method analysis (Latent Profile Analysis (LPA), Multi-level Latent Profile Analysis (MLPA) and Multi-level Logistic Regression Analysis (MLRA)) were used to identify ICT usage profiles. The study analysed data from 6,890 Turkish students across 186 schools participating in PISA 2018 (Program for International Student Assessment), revealing three distinct ICT usage profiles: Profile-1 (Low-Level ICT Users (19.06%)), Profile-2 (Intermediate-Level ICT Users (71.10%)), and Profile-3 (Advanced-Level ICT Users (9.84%)). The MLRA showed that students with low ICT usage have less access to ICT resources. Students in the Low-Level ICT Users profile also had lower scores on ICT-related motivation factors (interest, competence, social interaction, and autonomy). No significant effect of ICT usage on mathematics, reading, and science scores was observed. Variance differences at student and school levels could not be fully explained by covariates at the school level (type of school, ratio of computers connected to the internet per student, lack of educational materials and personnel). However, the ratio of computers per student effectively explained these differences. According to an MLPA, schools were categorised into two groups based on ICT resources: 'high' and 'low'. In schools with high ICT resources, the proportion of students in Profile-2 was found to be 45.8%, while those in Profile-3 accounted for 9%. In contrast, in schools with low ICT resources, the percentage of students in Profile-2 was 22.45%, and in Profile-3, it was 1.82%. These findings indicate that the level of a school's ICT resources significantly impacts students' technology usage skills. A significant finding of the research is that most Turkish students use ICT at an intermediate level at home for school lessons. The COVID-19 pandemic has further increased the importance of studying at home using ICT resources.

Programming Skills Recommendation System with Generative AI

In today’s rapidly evolving technological landscape, the demand for proficient programmers across various domains continues to surge. However, identifying and cultivating the right programming skills remains a daunting task for individuals seeking to enter or advance in the field. To address this challenge, our team has embarked on developing a Programming Skill Recommendation System (PSRS). The PSRS is envisioned as an intelligent platform leveraging machine learning algorithms and data analytics to provide personalized programming skill recommendations. By analysing diverse data sources such as user profiles, project requirements, industry trends, and skill proficiency.

Digital Skills: The Unavoidable Tool for Use of Academic Libraries during Covid-19

Aims: This study set out to establish the relationship between digital skills and the use of academic libraries in the Anglo-Saxon State Universities in Cameroon during the covid-19 period.
 Study Design: The study adopted a sequential explanatory mixed method research design.
 Place and Duration of Study: The study was carried out in the University of Bamenda Central Library and the University of Buea Library from 2020 to 2023.
 Methodology: A sample of 377 was selected from library staff and users through simple random sampling. Instruments for data collection were an interview guide, an observation guide and a questionnaire. Validity of instruments was guaranteed with the help of subject and language experts. Reliability was guaranteed by the use of Cronbach’s alpha and a value of .83 was attained. The data collection process was achieved using both direct delivery and electronic methods (Google Forms and Phone calls). Response rate for the questionnaire was 92.16% and for the interviews, 80%. Data from interviews were analysed thematically, from observations narratively and data from the questionnaire analysed using both descriptively (frequencies and percentages) and inferentially (Pearson correlation and simple linear regression).
 Results: The study found a positive correlation between use of academic libraries and digital skills (r(329) = .531, p < .01). Regression analysis showed that Digital Skills is statistically a significant predictor of the use of academic libraries (β = .632, t =7.269, p < .001). Challenges witnessed in relation to digital skills of library users and staff include technophobia, software, poor digital skills, and limited access to digital tools and insufficient equipment. The libraries under study made efforts to manage challenges through: networking, training, adopting new software and machines, and IT staff. These challenges therefore served as a barrier to the effective use of academic libraries.
 Conclusion: The study concludes that digital skills is a significant predictor of use of academic libraries in crises periods and if such challenges identified are not properly addressed, libraries are likely to register lower rates of patrons’ use and satisfaction.

A shiny R app for spatial analysis of species distribution models

In ecology, Species Distribution Models (SDMs) are a statistical tool whose use has expanded considerably over the last two decades. As their use has grown, so has the complexity of the data analysed and the structures of the models used.This has led to the development of various tools to facilitate the incorporation and use of these new data and statistical methodologies, mostly embodied in new R packages and Shiny applications that allow different types of SDMs to be solved. However, the Integrated Nested Laplace Approximation (INLA) approach, which has become increasingly popular in the field of ecological sciences, has not yet been integrated into an application that can synthesise the complexity of its code into a user-friendly interface for continuous spatial modelling.To overcome this shortcoming, we present in this paper a novel application, called BAYSPINS (BAYesian SPatial INla for SDMs), which allows the use of INLA for those who are not very experienced, or for those who are experienced and prefer a tool that allows them to carry out an initial analysis quickly, avoiding the process of writing code.BAYSPINS allows both geostatistical and preferential modelling, as well as a mixture of the two. It integrates the complex and hard coded SPDE-FEM (Stochastic Partial Differential Equation, along with the Finite Elements Method) approach to perform continuous spatial analysis with a visual interface. It also allows the use of default settings that automate the process or the customisation of a large number of elements that drive the modelling process. In this way, quick initial evaluations or more rigorous studies of the data provided by the user can be carried out, depending on the user's skill and understanding of the fundamentals underpinning the application.

Continuous Gesture Control of a Robot Arm: Performance Is Robust to a Variety of Hand-to-Robot Maps.

Despite advances in human-machine-interface design, we lack the ability to give people precise and fast control over high degree of freedom (DOF) systems, like robotic limbs. Attempts to improve control often focus on the static map that links user input to device commands; hypothesizing that the user's skill acquisition can be improved by finding an intuitive map. Here we investigate what map features affect skill acquisition. Each of our 36 participants used one of three maps that translated their 19-dimensional finger movement into the 5 robot joints and used the robot to pick up and move objects. The maps were each constructed to maximize a different control principle to reveal what features are most critical for user performance. 1) Principal Components Analysis to maximize the linear capture of finger variance, 2) our novel Egalitarian Principal Components Analysis to maximize the equality of variance captured by each component and 3) a Nonlinear Autoencoder to achieve both high variance capture and less biased variance allocation across latent dimensions Results: Despite large differences in the mapping structures there were no significant differences in group performance. Participants' natural aptitude had a far greater effect on performance than the map. Robot-user interfaces are becoming increasingly common and require new designs to make them easier to operate. Here we show that optimizing the map may not be the appropriate target to improve operator skill. Therefore, further efforts should focus on other aspects of the robot-user-interface such as feedback or learning environment.

Even short-term training improves the skills of novice exoscope users: a prospective laboratory experiment

BackgroundThe surgical 3D exoscopes have recently been introduced as an alternative to the surgical microscopes in microneurosurgery. Since the exoscope availability is still limited, it is relevant to know whether even a short-term exoscope training develops the skills needed for performing exoscope-assisted surgeries.MethodsTen participants (six consultants, four residents) performed two laboratory bypass test tasks with a 3D exoscope (Aesculap Aeos®). Six training sessions (6 h) were performed in between (interval of 2–5 weeks) on artificial models. The participants were divided into two groups: test group (n = 6) trained with the exoscope and control group (n = 4) with a surgical microscope. The test task was an artificial end-to-side microsurgical anastomosis model, using 12 interrupted 9–0 sutures and recorded on video. We compared the individual as well as group performance among the test subjects based on suturing time, anastomosis quality, and manual dexterity.ResultsAltogether, 20 bypass tasks were performed (baseline n = 10, follow-up n = 10). The median duration decreased by 28 min and 44% in the exoscope training group. The decrease was steeper (29 min, 45%) among the participants with less than 6 years of microneurosurgery experience compared to the more experienced participants (13 min, 24%). After training, the participants with at least 1-year experience of using the exoscope did not improve their task duration. The training with the exoscope led to a greater time reduction than the training with the microscope (44% vs 17%).ConclusionsEven short-term training with the exoscope led to marked improvements in exoscope-assisted bypass suturing among novice microneurosurgeons. For the more experienced participants, a plateau in the initial learning curve was reached quickly. A much longer-term effort might be needed to witness further improvement in this user group.

Exploring auditory emotion perception in cochlear implant users: Investigating the interplay of speech processing and affective signals

Human emotions are intricately expressed through vocal sounds, encompassing affective prosody in speech and non-verbal cues such as screams and laughter. Recent evidence indicates that vocalizations take neurophysiological precedence over speech-embedded emotions and are generally easier to identify. However, Cochlear implant (CI) users still face challenges deciphering the subtle nuances in these primal signals. The implant's limited fidelity in transmitting acoustic information results in highly variable levels of emotion perception abilities among its users. Identifying the factors explaining this significant variability in abilities among CI users remains of great interest. Our recent investigations into CI users' abilities to perceive emotions and speaker sincerity have often incorporated diverse aspects of auditory proficiency, including pitch discrimination, music processing, and speech intelligibility. The combination of results from these different projects can help shed light on the intricate interplay between speech processing and emotional recognition in CI users. Surprisingly, even when presented with emotional musical stimuli, CI users' proficiency often leaned toward processes related to speech intelligibility, proposing common mechanisms underlying linguistic and affective processes in CI users that do not readily relate to musical skills or pitch sensitivity. Hence, maintaining a clinical focus on speech processing remains crucial, even when exploring affective skills in CI users.

ACCOUNTING OUTSOURCING: CONTENT AND NEW REALITIES

Purpose. The aim of the article is to review the scientific interpretation of the concept of “accounting outsourcing” and its application in business processes of companies. Methodology of research. The research was conducted using a dialectical approach to the study of the current state of accounting development. General scientific and special methods are used, in particular: analysis, synthesis, induction, deduction and generalization as methods of scientific knowledge applied to the development of the provisions of the theory and practice of accounting outsourcing in the system of documentary and informational support of the main business processes of companies, monographic – when studying literary sources on accounting issues; epistemological method – to clarify and deepen the content of the “accounting outsourcing” category; system and analytical – when processing the received information; abstract and logical method – for formulating research conclusions. Findings. It was determined that in the conditions of decentralization of the company's business processes, introduction and development of new business concepts, approaches to the accounting methodology are changing, and the need to use accounting outsourcing is increasing. It is substantiated that the delegation of accounting responsibilities to specialized companies helps to change the functioning of the company's management and in accounting, in particular. It was found that the result of the development of accounting outsourcing will be the optimization of the organizational structure and functional capabilities of accounting, including through staff reduction, modernization of accounting processes and accounting policies in general; strengthening requirements for professional skills of users. Originality. A review of literary sources was carried out to clarify the meaning of the concept of “accounting outsourcing”, which made it possible to offer the latest understanding of the external accounting support of the company's business processes for the optimization of decentralized management functions. Practical value. The obtained results of the research will contribute to increasing the effectiveness of the formation and development of accounting outsourcing in modern conditions and will become the basis for further scientific developments in this field. Key words: accounting, accounting outsourcing, decentralization, business processes, specialized companies.

Exploring the Digital Divide in Open Education: A Comparative Analysis of Undergraduate Students

In the 21st century, the widespread use of information technologies has made access to technology, technology usage skills, and the quality of technology services increasingly important. However, the digital divide—defined as a lack of access to telecommunications—remains a significant issue that separates developed countries from developing countries. This study aimed to explore the digital divide in open education by comparing the digital divide levels of first term and last term or graduate students enrolled in the Anadolu University Open Education System. The study also examined how factors such as gender, age, income level, and employment status impact digital competency by comparing the digital divide scores of participants in these groups. The findings of the study suggest that first-term students have higher levels of digital competency than final-term students. The study also found that males, people aged 30–40, those with high incomes, and those working in the private sector had the highest digital competency scores. These results can be used to inform the development and implementation of open and distance learning programs to reduce the digital divide, as well as to identify specific groups that may be at a disadvantage in terms of digital competency.

Language Usage Skills of Social Media Users: Example of Instagram (April)

Her milletin tarihî ve kültürel değişiminin gözlemlendiği dil, birçok etkiden beslenerek gelişir. İnternetin doğuşuyla birlikte teknolojik gelişmelerin hayatımıza etkileri farklı alanlarda gözlemlenmektedir. Dil ve dilin kullanımı, bir milleti etkileyen faktörlerin başında gelen alanlardan biridir. Dilin etkilerini sözlü ve yazılı dil olarak iki açıdan görebiliriz. Türk dilinin ağızlarının rol aldığı konuşma diliyle yazı dili arasında birçok farklılık vardır. Günümüzdeki teknolojik cihazların kullanımının artmasıyla birlikte dijital ortamlarda kullanılan dil, yazı dili değil konuşma dili düzeyinde kalmaktadır. Çalışmanın konusu, sosyal medya kullanıcılarının dil kullanım becerilerini Instagram platformu üzerinden (Nisan) incelemektir. Çalışmada yöntem olarak nitel araştırma yöntemlerinden biri olan durum çalışması kullanılmıştır. Elde edilen veriler, doküman incelemesi yoluyla incelenmiştir. Veriler içerik analizi yöntemi kullanılarak analiz edilmiştir. Çalışmada Türkiye’de en çok takipçiye sahip ilk on hesap ele alınmış, Nisan ayı boyunca en çok yorum yapılan paylaşımlar tespit edilerek paylaşımın altına yapılan yorumlar dil kullanımı açısından (Türkçe) incelenmiştir. Çalışmada elde edilen veriler, imlayla ilgili kullanımlar ve dil bilgisi açısından incelemenin yer aldığı ses olayları olmak üzere iki başlık altında toplanmıştır. Türkiye’de en fazla takipçi sayısına sahip hesapların aylık (Nisan) paylaşımlarına yapılan yorumlarda; imlayla ilgili kullanımlarda klavye kaynaklı yazım hataları örneklerinin, dil bilgisi kullanımı başlığında ise bağlama görevli kelimenin kullanımı alt başlıklarında en fazla kullanım hatasının olduğu tespit edilmiştir.

Gaussian process regression approach for predicting wave attenuation through rigid vegetation

Numerical modelling in the coastal environment often requires highly skilled users and can be hindered by high computation costs and time requirements. Machine Learning (ML) techniques have the potential to overcome these limitations and complement existing methods. This is an exploratory investigation utilising a Gaussian Process (GP) data-driven modelling approach that can reproduce, for the given range of conditions in this study, the results of a widely used process-based model, XBeachX, when applied to the challenging problem of wave attenuation through vegetation. This study utilises efficient sampling strategies for data exploration, providing a valuable framework for future studies. The GP model was trained on a synthetic dataset generated using the numerical model XBeachX, which was calibrated using laboratory measurements. Our findings indicate that well-trained ML models can strongly complement traditional modelling approaches, especially in an environment where data sources are increasingly available. We have also explored the underlying interactions of the GP model's input features and their relationship to the model's output through a sensitivity analysis.

Time-dependant Bayesian knowledge tracing-Robots that model user skills over time.

Creating an accurate model of a user's skills is an essential task for Intelligent Tutoring Systems (ITS) and robotic tutoring systems. This allows the system to provide personalized help based on the user's knowledge state. Most user skill modeling systems have focused on simpler tasks such as arithmetic or multiple-choice questions, where the user's model is only updated upon task completion. These tasks have a single correct answer and they generate an unambiguous observation of the user's answer. This is not the case for more complex tasks such as programming or engineering tasks, where the user completing the task creates a succession of noisy user observations as they work on different parts of the task. We create an algorithm called Time-Dependant Bayesian Knowledge Tracing (TD-BKT) that tracks users' skills throughout these more complex tasks. We show in simulation that it has a more accurate model of the user's skills and, therefore, can select better teaching actions than previous algorithms. Lastly, we show that a robot can use TD-BKT to model a user and teach electronic circuit tasks to participants during a user study. Our results show that participants significantly improved their skills when modeled using TD-BKT.