The chapters of this thesis focus two different issues that arise in clinical trials and propose novel methods to address them. The first issue arises in the analysis of data with non-ignorable missing observations. The second issue concerns the development of methods that provide physicians better tools to understand and treat diseases efficiently by using each patient's characteristics and personal biomedical profile. Inherent to most clinical trials is the issue of missing data, specially those that arise when patients drop out the study without further measurements. Proper handling of missing data is crucial in all statistical analyses because disregarding missing observations can lead to biased results. In the first two chapters of this thesis, we deal with the "worst-rank score" missing data imputation technique in pretest-posttest clinical trials. Subjects are randomly assigned to two treatments and the response is recorded at baseline prior to treatment (pretest response), and after a pre-specified follow-up period (posttest response). The treatment effect is then assessed on the change in response from baseline to the end of follow-up time. Subjects with missing response at the end of follow-up are assign values that are worse than any observed response (worst-rank score). Data analysis is then conducted using Wilcoxon-Mann-Whitney test. In the first chapter, we derive explicit closed-form formulas for power and sample size calculations using both tied and untied worst-rank score imputation, where the worst-rank scores are either a fixed value (tied score) or depend on the time of withdrawal (untied score). We use simulations to demonstrate the validity of these formulas. In addition, we examine and compare four different simplification approaches to estimate sample sizes. These approaches depend on whether data from the literature or a pilot study are available. In second chapter, we introduce the weighted Wilcoxon-Mann-Whitney test on un-tied worst-rank score (composite) outcome. First, we demonstrate that the weighted test is exactly the ordinary Wilcoxon-Mann-Whitney test when the weights are equal. Then, we derive optimal weights that maximize the power of the corresponding weighted Wilcoxon-Mann-Whitney test. We prove, using simulations, that the weighted test is more powerful than the ordinary test. Furthermore, we propose two different step-wise procedures to analyze data using the weighted test and assess their performances through simulation studies. Finally, we illustrate the new approach using data from a recent randomized clinical trial of normobaric oxygen therapy on patients with acute ischemic stroke. The third and last chapter of this thesis concerns the development of robust methods for treatment groups identification in personalized medicine. As we know, physicians often have to use a trial-and-error approach to find the most effective medication for their patients. Personalized medicine methods aim at tailoring strategies for disease prevention, detection or treatment by using each individual subject's personal characteristics and medical profile. This would result to (1) better diagnosis and earlier interventions, (2) maximum therapeutic benefits and reduced adverse events, (3) more effective therapy, and (4) more efficient drug development. Novel methods have been proposed to identify subgroup of patients who would benefit from a given treatment. In the last chapter of this thesis, we develop a robust method for treatment assignment for future patients based on the expected total outcome. In addition, we provide a method to assess the incremental value of new covariate(s) in improving treatment assignment. We evaluate the accuracy of our methods through simulation studies and illustrate them with two examples using data from two HIV/AIDS clinical trials.

This dissertation focuses on the design of personalized and ubiquitous healthcare (PUH) services in the medical sector. It is proposed a new framework for structuring and deploying advanced PUH services in the right place, time and manner. According to this PUH framework, diverse types of entities (subjects and objects) are involved during the execution of each service. Each type of subject (e.g. patient, caregiver (doctor or nurse), volunteer, patient’s friend or relative, etc) or object (medical unit, medical files manager, etc) performs predefined actions according to the patient’s current health status and an agreed plan of actions. In the provision of PUH services, the permissible actions of each entity (or a group of entities) are determined by the “entity’s profile”, which is created in advance for this purpose. This work considers also the “group profile” that determines the behavior and the attributes of a specific group of entities. The PUH framework provides also mechanisms for the management of the patient’s context (environmental, living, etc) and the content of subject’s profile. Different profiling mechanisms are activated according to the subject’s type. Structurally, the proposed framework is an expansion of the framework that is utilized by the Next Generation Networks (NGN) (known as OSA/Parlay architecture) for the reliable provision of multipoint – multimedia communication services. The PUH framework distinguishes four classes of mechanisms: a) the conventional ETSI/Parlay mechanisms handling the communication among the entities that are involved during the execution of a PUH service, b) the mechanisms handling the acquisition of bio and contextual data by sensor networks deployed around the patient (e.g. Body Area Network), c) the mechanisms for the management of profiles data (e.g. availability, preferences, capabilities, care giving role, activities) and d) the security mechanisms. For the representation of these classes of mechanisms, an appropriate ontology has been created. Based on the above PUH framework, an entire profile management system is proposed. This system uses data from patient/caregivers profiles (or group profiles) in order to deploy a PUH service that will be able to support multi-party group-working schemes with well defined behaviors of all involved entities, devices and services. The technology of smart cards has selected as the appropriate technology for creating, accessing and enriching the subjects profiles. A prototype of the proposed profile management system is implemented using the cloud computing technology (Windows Azure platform). We have considered that parts of a profile are located in different service providers. The efficiency of the developed profile management system is evaluated in terms of time response in order to select the appropriate healthcare provider by simulating system's response to real world scenarios. / Η παρούσα διατριβή εστιάζεται στο σχεδιασμό εξατομικευμένων (personalized) και διάχυτων / πανταχού παρουσών (ubiquitous) υπηρεσιών τηλεϊατρικής κατάλληλων για την υγειονομική περίθαλψη χρόνια πασχόντων ασθενών (Personalized and Ubiquitous Healthcare - PUH). Προτείνεται ένα νέο πλαίσιο δημιουργίας προηγμένων υπηρεσιών PUH και παροχή των υπηρεσιών αυτών στο σωστό τόπο και χρόνο, σύμφωνα με το «προφίλ» του ασθενή. Το προφίλ αυτό περιγράφει τις δυνατές καταστάσεις όπου μπορεί να βρεθεί η υγεία του (κανονική, σε κίνδυνο, κλπ), τον τύπο υπηρεσίας PUH που θα πρέπει να λάβει ανά κατάσταση, το περιβάλλον διαβίωσής του, τις προτιμήσεις του, κλπ. Το πλαίσιο PUH επιτρέπει σε διαφορετικούς τύπους υποκειμένων (π.χ. ασθενής, πάροχος φροντίδας (γιατρός ή νοσοκόμα), εθελοντής, φίλος του ασθενή ή συγγενής, κ.λπ.) και αντικειμένων (ιατρική μονάδα, διαχειριστής ιατρικών αρχείων, κ.λ.π.) να εμπλέκονται ενεργά κατά τη διάρκεια της εκτέλεσης κάθε υπηρεσίας προσφέροντας ειδικού τύπου υπηρεσίες. Η ταυτότητα και η συμπεριφορά του κάθε υποκειμένου και αντικειμένου περιγράφεται από ένα ατομικό «προφίλ οντότητας» μέσα στο οποίο καθορίζονται: α) τα είδη των υπηρεσιών που υποστηρίζει η οντότητα ανάλογα με την κατάσταση της υγείας του ασθενή και β) οι τύποι των ενεργειών που επιτρέπεται να εκτελεί η οντότητα ανά υπηρεσία. Στη διατριβή μοντελοποιείται επίσης το «προφίλ ομάδας» που καθορίζει συνολικά τη συμπεριφορά μιας συγκεκριμένης ομάδας οντοτήτων που εμπλέκεται στην παροχή της υπηρεσίας PUH. Το πλαίσιο PUH παρέχει επίσης μηχανισμούς διαχείρισης του περιεχομένου του προφίλ του ασθενή και του κάθε εμπλεκόμενου υποκειμένου ανά υπηρεσία PUH. Διαφορετικοί μηχανισμοί προφίλ ενεργοποιούνται ανάλογα με τον τύπο του υποκειμένου. Δομικά το προτεινόμενο πλαίσιο είναι μια επέκταση του πλαισίου OSA Parlay που χρησιμοποιείται από τα δίκτυα επόμενης γενεάς (NGN) για την αξιόπιστη παροχή πολυσημειακών / πολυμεσικών υπηρεσιών επικοινωνίας. Το πλαίσιο PUH διακρίνει τέσσερις κατηγορίες μηχανισμών: α) τους συμβατικούς μηχανισμούς ETSI/ Parlay που χειρίζονται την επικοινωνία μεταξύ των οντοτήτων που λαβαίνουν μέρος κατά τη διάρκεια της εκτέλεσης μιας υπηρεσίας PUH, β) τους μηχανισμούς που χειρίζονται την απόκτηση βιοσημάτων και στοιχείων του περιβάλλοντος του ασθενή από δίκτυα αισθητήρων που εκτείνονται γύρω από τον ασθενή (π.χ. δίκτυο περιοχής σώματος), γ) τους μηχανισμούς διαχείρισης των στοιχείων των προφίλ (π.χ. διαθεσιμότητα, προτιμήσεις, ικανότητες, ρόλος, δραστηριότητες) και δ) τους μηχανισμούς ασφάλειας. Για την αναπαράσταση αυτών των κατηγοριών μηχανισμών, έχει δημιουργηθεί μια κατάλληλη οντολογία. Με βάση το ανωτέρω πλαίσιο PUH, προτείνεται ένα ολόκληρο σύστημα διαχείρισης των προφίλ. Το σύστημα αυτό χρησιμοποιεί στοιχεία από τα προφίλ των ασθενών και των παρόχων φροντίδας (ή το προφίλ της ομάδας) προκειμένου να δημιουργηθεί μια υπηρεσία PUH που να είναι σε θέση να υποστηρίξει σχήματα πολλαπλών ομάδων εργασίας, με καλά καθορισμένες συμπεριφορές όλων των εμπλεκόμενων οντοτήτων, συσκευών και υπηρεσιών. Η τεχνολογία των έξυπνων καρτών έχει επιλεγεί ως η κατάλληλη τεχνολογία για τη δημιουργία, πρόσβαση και ενημέρωση των εμπλεκομένων προφίλ. Τέλος, έχει αναπτυχθεί ένα πρωτότυπο του προτεινόμενου συστήματος διαχείρισης των προφίλ με χρήση της τεχνολογίας του υπολογιστικού σύννεφου (cloud computing) – Windows Azure platform. Έχουμε θεωρήσει ότι τα τμήματα ενός προφίλ βρίσκονται σε διαφορετικούς παρόχους υπηρεσιών. Η αποδοτικότητα του αναπτυγμένου συστήματος διαχείρισης προφίλ αξιολογείται σε σχέση με τη χρονική απόκριση προκειμένου να επιλεγεί ο αρμόδιος πάροχος υγειονομικής περίθαλψης προσομοιώνοντας τη λειτουργία και απόκριση του συστήματος σε πραγματικά σενάρια.

Internet Protocol TV (IPTV) delivers television content to users over IP-based network. Different from the traditional TV services, IPTV platforms provide users with large amount of multimedia contents with interactive and personalized services, including the targeted advertisement, on-demand content, personal video recorder, and so on. IPTV is promising since it allows to satisfy users experience and presents advanced entertainment services. On the other hand, the Next Generation Network (NGN) approach in allowing services convergence (through for instance coupling IPTV with the IP Multimedia Subsystem (IMS) architecture or NGN Non-IMS architecture) enhances users' experience and allows for more services personalization. Although the rapid advancement in interactive TV technology (including IPTV and NGN technologies), services personalization is still in its infancy, lacking the real distinguish of each user in a unique manner, the consideration of the context of the user (who is this user, what is his preferences, his regional area, location, ..) and his environment (characteristics of the users' devices 'screen types, size, supported resolution, '' and networks available network types to be used by the user, available bandwidth, ..') as well as the context of the service itself (content type and description, available format 'HD/SD', available language, ..) in order to provide the adequate personalized content for each user. This advanced IPTV services allows services providers to promote new services and open new business opportunities and allows network operators to make better utilization of network resources through adapting the delivered content according to the available bandwidth and to better meet the QoE (Quality of Experience) of clients. This thesis focuses on enhanced personalization for IPTV services following a user-centric context-aware approach through providing solutions for: i) Users' identification during IPTV service access through a unique and fine-grained manner (different from the identification of the subscription which is the usual current case) based on employing a personal identifier for each user which is a part of the user context information. ii) Context-Aware IPTV service through proposing a context-aware system on top of the IPTV architecture for gathering in a dynamic and real-time manner the different context information related to the user, devices, network and service. The context information is gathered throughout the whole IPTV delivery chain considering the user domain, network provider domain, and service/content provider domain. The proposed context-aware system allows monitoring user's environment (devices and networks status), interpreting user's requirements and making the user's interaction with the TV system dynamic and transparent. iii) Personalized recommendation and selection of IPTV content based on the different context information gathered and the personalization decision taken by the context-aware system (different from the current recommendation approach mainly based on matching content to users' preferences) which in turn highly improves the users' Quality of Experience (QoE) and enriching the offers of IPTV services

Adaptyviose sistemose prisitaikymas prie besimokančiojo yra paremtas duomenų apie besimokantįjį rinkimu, analizavimu ir mokymosi aplinkos pritaikymu besimokančiojo poreikiams. Tam būtina parinkti tokius „sekimo“ duomenis, pagal kuriuos būtų galima daryti išvadas sistemos lygmenyje. Šie duomenys turi būti suprantami sistemai, nuolat atnaujinami, lengvai surenkami. Jie gali būti įvairūs, pradedant nuorodų paspaudimo laiku, baigiant akies žvilgsnio nukreipimo vieta. Pagal tai sistema gali transformuoti duomenis ir – priklausomai nuo savo paskirties – duoti patarimus ar tam tikromis priemonėmis pavaizduoti naudingą informaciją, tuo pačiu atsižvelgdama į rezultatus. Tačiau daugelis šių sistemų yra tik prototipo stadijoje arba naudojamos nesudėtingiems procesams vykdyti. Mums žinomos adaptyvios sistemos yra skirtos vieno dalyko probleminei sričiai. Šiame darbe tirsime besimokančiojo modelio perteikimo galimybę virtualioje mokymo(si) aplinkoje (VMA), kai besimokantysis dalyvauja viename arba keliuose nuotoliniuose kursuose. / In adaptive systems adaptation to learner is defined by collection of data about learner, collected data analysis and learning environment adaptation to learners needs. Looking forward to this goal it is necessary to select such logging data, which can be used to make conclusions in a system level. Such data should be acceptable to system, interactive and easy to collect. Data used can be various, starting from click time of the link ending with eye look direction angle. Such system can provide data transformations and depending on purpose, give suggestions. Using necessary tools depict useful information, reacting to results. Most of currently build systems are only in prototype stage or are used for unsophisticated process. Most of them are one subject systems. In this work we address a possibility of student model’s depiction in a VLE, when student participate in one or more than one distance course.

Understanding variability of heath status is highly likely to be an important component of personalized medicine to predict health status of individuals and to promote personal health. Evidences of Genome Wide Association Study and gene expression study indicating that genetic factors affect the risk susceptibility of individuals have suggested adding genetic factors as a component of health status measurements. In order to validate or to predict health risk status with collected personal data such as clinical measurements or genomic data, it is important to have a well-established profile of diseases. The primary effort of this work was to find genomic evidence relevant to coronary artery disease. Two major methods of genomic analysis, gene expression profiling and GWAS on gene expression, were performed to dissect transcriptional and genotypic fingerprints of coronary artery disease. Blood-informative transcriptional Axes that can be described by 10 covariating transcripts per each Axis were utilized as a crucial measure of gene expression analysis. This study of the relationship between gene expression variation and various measurements of coronary artery disease delivered compelling results showing strong association between two transcriptional Axes and incident of myocardial infarction. 244 transcripts closely correlated with death by cardiovascular disease related events were also showing clear association with those two transcriptional Axes. These results suggest potential transcripts for use in risk prediction for the advent of myocardial infarction and cardiac death.

The present study evaluated the use of a self-instructional manual supported by a computer-aided personalized system of instruction (CAPSI) for teaching Discrete-Trials Teaching (DTT) to university students. Prior to studying the manual, five participants taught three tasks, commonly taught to children with Autism Spectrum Disorders (ASD), to a confederate role-playing a child with an ASD. Using the Discrete-Trials Teaching Evaluation Form (DTTEF), the main researcher assessed the participants’ ability to perform DTT accurately. Subsequently, participants studied a self-instructional manual using CAPSI to demonstrate mastery of study questions about DTT. Finally, participants once again attempted to teach the three tasks to a confederate role-playing a child with an ASD. Overall mean baseline accuracy on the DTTEF was 54.86%, and improved to 84.73% in post-treatment, a 30% improvement. Participants’ self-recorded study time was an average of 12 hours and 48 minutes. The results suggest that CAPSI is an effective educational tool for the delivery of the self-instructional manual. Future research should investigate (1) how to make CAPSI even more effective, and (2) whether these results can be generalized to other populations such as ABA tutors, parents, and paraprofessionals working with children with ASD.

Organizations own data sources that contain millions, billions or even trillions of rows and these data are usually highly dimensional in nature. Typically, these raw repositories are comprised of numerous independent data sources that are too big to be copied or joined, with the consequence that aggregations become highly problematic. Data cubes play an essential role in facilitating fast Online Analytical Processing (OLAP) in many multi-dimensional data warehouses. Current data cube computation techniques have had some success in addressing the above-mentioned aggregation problem. However, the combined problem of reducing data cube size for very large and highly dimensional databases, while guaranteeing fast query response times, has received less attention. Another issue is that most OLAP tools often causes users to be lost in the ocean of data while performing data analysis. Often, most users are interested in only a subset of the data. For example, consider in such a scenario, a business manager who wants to answer the crucial location-related business question. "Why are my sales declining at location X"? This manager wants fast, unambiguous location-aware answers to his queries. He requires access to only the relevant ltered information, as found from the attributes that are directly correlated with his current needs. Therefore, it is important to determine and to extract, only that small data subset that is highly relevant from a particular user's location and perspective. In this thesis, we present the Personalized Smart Cube approach to address the abovementioned scenario. Our approach consists of two main parts. Firstly, we combine vertical partitioning, partial materialization and dynamic computation to drastically reduce the size of the computed data cube while guaranteeing fast query response times. Secondly, our personalization algorithm dynamically monitors user query pattern and creates a personalized data cube for each user. This ensures that users utilize only that small subset of data that is most relevant to them. Our experimental evaluation of our Personalized Smart Cube approach showed that our work compared favorably with other state-of-the-art methods. We evaluated our work focusing on three main criteria, namely the storage space used, query response time and the cost savings ratio of using a personalized cube. The results showed that our algorithm materializes a relatively smaller number of views than other techniques and it also compared favourable in terms of query response time. Further, our personalization algorithm is superior to the state-of-the art Virtual Cube algorithm, when evaluated in terms of the number of user queries that were successfully answered when using a personalized cube, instead of the base cube.

Amningsfrekvensen har i Sverige successivt minskat för varje år och statistik visar kortare amningstid idag än för tio år sedan. Bröstmjölk är den ideala födan för barnet under de första sex månaderna. Den skyddar barnet mot ohälsa samt ökar överlevnaden. En betydelsefull del av arbetet för BVC-sjuksköterskorna är stödja och främja amning samt uppmuntra till upprätthållande av amning. Syftet med studien var att undersöka BVC-sjuksköterskors erfarenhet av amningsrådgivning. En kvalitativ forskningsmetod med deskriptiv design och induktiv ansats har använts. Specialistsjuksköterskor som arbetade på BVC intervjuades för besvarande av studiens syfte. Intervjumaterialet bearbetades med kvalitativ innehållsanalys. I resultatet framkom tre kategorier: Amningsrådgivningen baseras på riktlinjer, Behov av individanpassat stöd och Svårt och tidskrävande med amningsrådgivning. I studien framkom det att samtliga BVC-sjuksköterskor använde riktlinjer i amningsrådgivningen samt kompletterade dessa med annan kunskap och litteratur. BVC-sjuksköterskorna gjorde en individuell anpassning av amningsrådgivningen för att tillgodose mödrarnas personliga önskemål. BVC-sjuksköterskorna beskrev amningsrådgivningen som svår och tidskrävande. Resultatet av denna studie bidrar till insikt i vikten av kontinuerligt uppdaterade och förbättrade amningsriktlinjer samt ger en förståelse för BVC-sjuksköterskornas svårigheter med amningsrådgivningen. Studien kan också bidra till en ökad medvetenhet hos BVC-sjuksköterskorna av mödrarnas behov av individanpassad amningsrådgivning. / The breastfeeding rate has gradually declined in Sweden every year and statistics show shorter breastfeeding today than ten years ago. Breast milk is the ideal food for the baby during the first six months. It protects the baby against illness and increase survival. A significant part of the work for the nurses at child health service is to support and promote breastfeeding and encourage the maintenance of lactation. The aim of the study was to investigate the child health service nurses' experience of breastfeeding counseling. Qualitative research with descriptive design and inductive approach has been used. Specialist nurses working in child health service were interviewed for answering the study's purpose. The interview data were processed using qualitative content analysis. The results revealed three categories: Breastfeeding counseling based on guidelines, Need for personalized support and Difficult and time consuming with breastfeeding counseling. The study revealed that all child health service nurses used guidelines in breastfeeding counseling and supplemented these with other knowledge and literature. Nurses at child health service made an individual adjustment of breastfeeding counseling to meet the mothers' personal preferences. The child health service nurses described the breastfeeding counseling as difficult and time-consuming. The results of this study contributes to the understanding of the importance of continuously updated and improved breastfeeding guidelines, and provides an understanding of the child health service nurses' difficulties with breastfeeding counseling. The study may also contribute to an increased awareness for the child health service nurses, of the mothers' need for individualized breastfeeding counseling.

Tecnologia Assistiva é o termo atualmente utilizado para definir uma enorme variedade de produtos e serviços destinados a pessoas com deficiências. O design de produto de equipamentos de tecnologias assistivas segue diferentes rotas tecnológicas, com produtos fabricados em série ou personalizados. Tais equipamentos objetivam otimizar e potencializar as funções corporais alteradas e, com isso, reconduzir essas pessoas às mais variadas atividades sociais. Neste sentido, esta pesquisa teve como proposta contribuir na construção de novas rotas tecnológicas para a fabricação de assentos e encostos personalizados para pessoas deficientes e usuários cadeira de rodas. A metodologia conceitual incluiu nesta pesquisa as ferramentas de digitalização tridimensional, usinagem CNC e termografia para realizar medidas e analisar os assentos e encostos personalizados fabricados a partir de dados antropométricos individualizados. Os protótipos projetados, fabricados e sistematicamente testados geraram resultados indicativos de que os modelos personalizados propostos são válidos, visto que agregam diferenciais como; uma maior distribuição das cargas, e também pela distribuição das temperaturas corporais obtidas pelas superfícies e contornos reproduzidos pelos equipamentos segundo a anatomia de cada pessoa estudada. Assim, as principais contribuições deste estudo estão na otimização e simplificação do processo de fabricação, e no baixo custo das matérias primas utilizadas na pesquisa. Finalmente, os resultados indicam que os produtos obtidos, assentos personalizados, podem beneficiar inúmeras pessoas deficientes, mesmo que apresentem uma anatomia diferenciada, sobretudo os cadeirantes por passarem vários períodos sentados, e esta tecnologia assistiva possibilita a redução dos riscos de lesões teciduais por aumentarem a área de contato, e assim distribui com eficácia a temperatura e peso corporal. / Assistive technology is the currently used term to define a wide range of services and products aimed at disabled persons. Design for assistive technology devices is seen in two different technology pathways, with serial and personalized products. These devices seek to optimize impaired body functions and, thus, reinsert these persons in various social activities. This study aims to contribute to the construction of new technology ruts for the production of personalized seats and backrests for wheelchairs. The methodology includes the application of the concepts of three-dimensional digitalization, CNC Machining, and thermography in order to create and analyze personalized seats and backrests produced from individualized anthropometric data. The results obtained show that the proposed models are valid, because they permit a wider distribution of bodily weight and temperature through the outlines inserted in the equipments according to each person’s anatomy. The greatest contribution of this study is its simplicity of production and the low cost of materials used in the research, which may benefit numerous wheelchair users who present unique anatomies, reducing the risks of tissue lesions by enlarging the area of contact, which results in a more effective distribution of bodily temperature and weight.

abstract: This study was conducted to assess the performance of 176 students who received algebra instruction through an online platform presented in one of two experimental conditions to explore the effect of personalized learning paths by comparing it with linearly flowing instruction. The study was designed around eight research questions investigating the effect of personalized learning paths on students’ learning, intrinsic motivation and satisfaction with their experience. Quantitative results were analyzed using Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA) and split-plot ANOVA methods. Additionally, qualitative feedback data were gathered from students and teachers on their experience to better explain the quantitative findings as well as improve understanding of how to effectively design an adaptive personalized learning platform. Quantitative results of the study showed no statistical difference between students assigned to treatments that compared linear and adaptive personalized instructional flows. The lack of significant differences was explained by two main factors: (a) low usage and (b) platform and content related issues. Low usage may have prevented students from being exposed to the platforms long enough to create a potential for differences between the groups. Additionally, the reasons for low usage may in part be explained by the qualitative findings, which indicated that unmotivated and tired teachers and students were not very enthusiastic about the study because it occurred near the end of school year. Further, computer access was a challenging issue at the school throughout the study. On the other hand, platform and content related issues worked to inhibit the potential beneficial effects of the platforms. The three prominent issues were: (a) the majority of the students found the content boring or difficult, (b) repeated recommendations from the adaptive platform created frustration, and (c) a barely moving progress bar caused disappointment among participants. / Dissertation/Thesis / Doctoral Dissertation Educational Technology 2015