Active learning strategies are important for facilitating deep learning that may be carried throughout life, but which is still finding its way into the college setting. Educators are not often trained in effective learning practices, which reduces the cognitive and proficiency gains of their students. By providing such guidance in the formative years of a teacher’s training, we hypothesize that the learning environment will be greatly enriched and enhanced. On the opposite end of the spectrum of life and cognition, the plague of dementia also warrants examination. Alzheimer’s disease (AD), an incurable neurodegenerative disorder progressing from the medial temporal lobe, is the most common form of dementia diagnosed in people over age 65, afflicting 30-40% of those 85 years and older. Despite its prevalence, effective treatments are limited because the principal causes and triggers of AD are not entirely understood. Growing evidence demonstrates that oxidative stress (OS) is an important factor contributing to the initiation and progression of AD. A key player contributing to this OS is iron, an essential trace mineral which is required for proper neuronal function, but which generates reactive oxygen species during redox transitions. Intracellular labile iron pool (LIP) levels are strictly regulated by proteins such as transferrin (import), ferroportin (export), and ferritin (storage). However, when these proteins become dysregulated, excess iron associates with other proteins such as amyloid beta (Aβ) and tau, aggregations of which are hallmarks of AD. In our hypothetical model, under extensive or prolonged OS, as occurs in AD, much larger Aβ plaques form because the stress does not abate. Hyperphosphorylated tau is the last resort to protect the cell against free iron, and aggregates when the LIP is elevated because neither iron storage in ferritin nor iron export through ferroportin can relieve the neurons of the free iron.

With the increasingly widespread adoption of online learning, education is at an important crossroads. Spirituality and character building were once an important part of formal education. In the more secular modern era, many institutions of higher learning have neglected the spiritual aspects of teaching and learning. There is increasing academic interest in the relationship between spirituality and education. At the same time, relatively little attention has been paid to how spiritual and character development can be facilitated in online courses. This study seeks to better understand the how to develop spirituality and character building more effectively in online education through three related studies. The first article explores published research related to spirituality and education. Definitions are derived for two different perspectives, a contemporary North American view, and the Brigham Young University view. A second article reports on a quantitative analysis of how spiritually strengthening and character building, both Aims of a BYU Education, were accomplished in 63 online courses taught recently at BYU from the perspective of approximately 1730 students. The third article, “Spiritual and Character Development in Online Education from the Instructors’ Perspective”, qualitatively investigates the actions of instructors to more effectively accomplish these two Aims in their online courses based on their self-reported responses to six open-ended questions. Students responded to 77 questions (using 7-point Likert Scales) related to these two Aims. Structural Equation Modeling showed four constructs as having significant influence on their spiritual and character development: genuine caring for students (by teachers), Gospel connections, instructor’s morality, and ethics in relation to the course. Twelve subfactors of social, cognitive and teacher presence, and student engagement indicated these four subfactors related to spiritual and character development. Instructors that are more intentional and explicit also utilize active learning techniques. These ask students to do more than just read about or talk about spirituality and character development. Rather, they involve students in active learning activities such as reflecting on ethics, creating personal value statements/constitutions, and setting and periodically reporting on related goals.

<p>The active learning literature lacks systematic investigations into whether the amount of active learning implemented in class and the ordering of lecture and active learning make a difference in how much students learn in STEM disciplines. Therefore, I investigated how the dosage amount and schedule of lecture and active learning affect student learning of science content. The first experiment involved 146 subjects who learned about biological taxonomies through either a lecture (100% lecture/0% active learning) or an active learning activity (0% lecture/100% active learning). Results indicated that subjects in the pure lecture condition scored 20.27 percentage points higher on the posttest as compared to the pure active learning condition; these results held across different question types. Further, the pure lecture condition did not significantly differ from the pure active learning condition on subjects’ judgements of learning and their satisfaction with the instructional mode they received. The second experiment involved 219 subjects who learned about biological taxonomies through a lecture, a lecture and active learning activity that were interspersed (alternation between lecture and the active learning activity), or a lecture and active learning activity that were blocked (all lecture done before the active learning activity). Results indicated that subjects in the interspersed condition scored significantly higher than subjects in the blocked and pure lecture conditions (by 10.96 and 13.95 percentage points, respectively); these results generally held across different question types. Further, the pure lecture condition was significantly lower than the interspersed and blocked conditions on subjects’ judgements of learning and their satisfaction with the lecture. Based on these two experiments, it may not be a question of whether to choose lecture or active learning but rather a question of how to integrate them to maximize their benefits.</p>

The fields of biologically inspired artificial intelligence, neuroscience, and psychology have had exciting influences on each other over the past decades. Especially recently, with the increased popularity and success of artificial neural networks (ANNs), ANNs have enjoyed frequent use as models for brain function. However, there are still many disparities between the implementation, algorithms, and learning environment used for deep learning and those employed by the brain, which is reflected in their differing abilities. I first briefly introduce ANNs and survey the differences and similarities between them and the brain. I then make a case for designing the learning environment of ANNs to be more similar to that in which brains learn, namely by allowing them to actively interact with the world and decreasing the amount of external supervision. To implement this sensorimotor learning in an artificial agent, I use deep reinforcement learning, which I will also briefly introduce and compare to learning in the brain. In the research presented in this dissertation, I focus on testing the hypothesis that the learning environment matters and that learning in an embodied way leads to acquiring different representations of the world. We first tested this on human subjects, comparing spatial knowledge acquisition in virtual reality to learning from an interactive map. The corresponding two publications are complemented by a methods paper describing eye tracking in virtual reality as a helpful tool in this type of research. After demonstrating that subjects do indeed learn different spatial knowledge in the two conditions, we test whether this transfers to artificial agents. Two further publications show that an ANN learning through interaction learns significantly different representations of the sensory input than ANNs that learn without interaction. We also demonstrate that through end-to-end sensorimotor learning, an ANN can learn visually-guided motor control and navigation behavior in a complex 3D maze environment without any external supervision using curiosity as an intrinsic reward signal. The learned representations are sparse, encode meaningful, action-oriented information about the environment, and can perform few-shot object recognition despite not knowing any labeled data beforehand. Overall, I make a case for increasing the realism of the computational tasks ANNs need to solve (largely self-supervised, sensorimotor learning) to improve some of their shortcomings and make them better models of the brain.

With the increasingly widespread adoption of online learning, education is at an important crossroads. Spirituality and character building were once an important part of formal education. In the more secular modern era, many institutions of higher learning have neglected the spiritual aspects of teaching and learning. There is increasing academic interest in the relationship between spirituality and education. At the same time, relatively little attention has been paid to how spiritual and character development can be facilitated in online courses. This study seeks to better understand the how to develop spirituality and character building more effectively in online education through three related studies. The first article explores published research related to spirituality and education. Definitions are derived for two different perspectives, a contemporary North American view, and the Brigham Young University view. A second article reports on a quantitative analysis of how spiritually strengthening and character building, both Aims of a BYU Education, were accomplished in 63 online courses taught recently at BYU from the perspective of approximately 1730 students. The third article, “Spiritual and Character Development in Online Education from the Instructors’ Perspective”, qualitatively investigates the actions of instructors to more effectively accomplish these two Aims in their online courses based on their self-reported responses to six open-ended questions. Students responded to 77 questions (using 7-point Likert Scales) related to these two Aims. Structural Equation Modeling showed four constructs as having significant influence on their spiritual and character development: genuine caring for students (by teachers), Gospel connections, instructor’s morality, and ethics in relation to the course. Twelve subfactors of social, cognitive and teacher presence, and student engagement indicated these four subfactors related to spiritual and character development. Instructors that are more intentional and explicit also utilize active learning techniques. These ask students to do more than just read about or talk about spirituality and character development. Rather, they involve students in active learning activities such as reflecting on ethics, creating personal value statements/constitutions, and setting and periodically reporting on related goals.

Background Drug utilization review (DUR) is a central role of the pharmacist, especially within the community pharmacy setting. Previous literature has shown risk of “alert fatigue”, supporting the necessity of pharmacists to utilize a step-wise approach in evaluation of drug therapy during the verification process. Many students are intimidated by this process, and may lack verification practice or experience until their first day as a licensed pharmacist. Educational Activity and Setting An innovative skills-based laboratory exercise was developed for third-year pharmacy students to develop DUR skills. Through simulation of patient prescriptions, profiles, and drug information resources, students were tasked with completing a DUR for each patient case. Students were expected evaluate the clinical significance of various drug-related problems, determine if they would or would not dispense the prescription, and were required to provide rationale for their decision. Findings This learning activity was well-received by the student population; however, students struggled with the volume of cases along with identifying a solution to the clinical scenario. On average, students required nine minutes per case, which is likely longer than community pharmacists can devote to a single DUR in practice. Discussion In response, to student challenges with the activity, the number of cases was condensed to highlight key concepts and cases that facilitated strong discussion. To improve students’ approach to the DUR process, faculty developed a vodcast to watch prior to the activity explaining a systematic approach to the DUR process as well as considerations a pharmacist should have. Summary Development and integration of an active-learning, simulated dispensing activity allowed students to gain valuable experience completing the DUR process, a foundational community pharmacy practice skill; however, repeated experience should be provided to ensure competency.

This study is a study of literature which focused on the research question How can cooperative learning reduced perceived mathematics anxiety. This was conducted via a literature search in a variety of databases, such as ERC, ERIC, and finally libsearch. The searchwords that were used were connected to the reasearch question, for instance cooperative learning in mathematics and anxiety. The studies that were chosen based on relevance were then analyzed and summarized. Based on the summarization subcategories such as shared responsibility, complement each other, helping, not competing, active learning, and setbacks were established based on recurring concepts. The results were then presented based on these subcategories’ effect on perceived mathematics anxiety. The conclusion that was made was that cooperative learning can reduce mathematics anxiety by giving students an improved sense of responsibility, cooperation, and support by their peers as well as creating a less competitive environment with more focus on active learning

Recommendation systems have been widely utilized in e-commerce settings to aid users through their shopping experiences. The principal advantage of these systems is their ability to narrow down the purchase options in addition to marketing items to customers. However, a number of challenges remain, notably those related to obtaining a clearer understanding of users, their profiles, and their preferences in terms of purchased items. Specifically, recommender systems based on collaborative filtering recommend items that have been rated by other users with preferences similar to those of the targeted users. Intuitively, the more information and ratings collected about the user, the more accurate are the recommendations such systems suggest. In a typical recommender systems database, the data are sparse. Sparsity occurs when the number of ratings obtained by the users is much lower than the number required to build a prediction model. This usually occurs because of the users’ reluctance to share their reviews, either due to privacy issues or an unwillingness to make the extra effort. Grey-sheep users pose another challenge. These are users who shared their reviews and ratings yet disagree with the majority in the systems. The current state-of-the-art typically treats these users as outliers and removes them from the system. Our goal is to determine whether keeping these users in the system may benefit learning. Thirdly, cold-start problems refer to the scenario whereby a new item or user enters the system and is another area of active research. In this case, the system will have no information about the new user or item, making it problematic to find a correlation with others in the system. This thesis addresses the three above-mentioned research challenges through the development of machine learning methods for use within the recommendation system setting. First, we focus on the label and data sparsity though the development of the Hybrid Cluster analysis and Classification learning (HCC-Learn) framework, combining supervised and unsupervised learning methods. We show that combining classification algorithms such as k-nearest neighbors and ensembles based on feature subspaces with cluster analysis algorithms such as expectation maximization, hierarchical clustering, canopy, k-means, and cascade k-means methods, generally produces high-quality results when applied to benchmark datasets. That is, cluster analysis clearly benefits the learning process, leading to high predictive accuracies for existing users. Second, to address the cold-start problem, we present the Popular Users Personalized Predictions (PUPP-DA) framework. This framework combines cluster analysis and active learning, or so-called user-in-the-loop, to assign new customers to the most appropriate groups in our framework. Based on our findings from the HCC-Learn framework, we employ the expectation maximization soft clustering technique to create our user segmentations in the PUPP-DA framework, and we further incorporate Convolutional Neural Networks into our design. Our results show the benefits of user segmentation based on soft clustering and the use of active learning to improve predictions for new users. Furthermore, our findings show that focusing on frequent or popular users clearly improves classification accuracy. In addition, we demonstrate that deep learning outperforms machine learning techniques, notably resulting in more accurate predictions for individual users. Thirdly, we address the grey-sheep problem in our Grey-sheep One-class Recommendations (GSOR) framework. The existence of grey-sheep users in the system results in a class imbalance whereby the majority of users will belong to one class and a small portion (grey-sheep users) will fall into the minority class. In this framework, we use one-class classification to provide a class structure for the training examples. As a pre-assessment stage, we assess the characteristics of grey-sheep users and study their impact on model accuracy. Next, as mentioned above, we utilize one-class learning, whereby we focus on the majority class to first learn the decision boundary in order to generate prediction lists for the grey-sheep (minority class). Our results indicate that including grey-sheep users in the training step, as opposed to treating them as outliers and removing them prior to learning, has a positive impact on the general predictive accuracy.

The technological improvements and a generation with increased interest in using technology to aid in their learning. Cause a need for a change in the educational approaches or already established methodologies. The modern educational approach hints a move from the traditional passive learning approach, where the students are passive listeners, into an active learning approach, where the students access the information beforehand. Therefore, classroom time is used to elaborate on complex subjects through an active discussion during the lectures. Student Response Systems (SRS) aims to integrate technological tools with the educational environment, thereby improving the students' participation and engagement. The purpose of this thesis is to study the factors influencing the students' engagement when using SRS in a flipped classroom environment. Furthermore, to what extend can the SRS facilitate the students' active participation in the discussion within an educational context. The research is performed at Linnaeus University in a course at a Master level course. A pre-study was conducted, consisting of observing the course later to form the interview question from the acquired knowledge. Afterward, interviews were conducted with 7 of the participating students. The results of the study might provide additional knowledge for the teachers to decide upon an approach to implement the use of SRS with the flipped classroom approach.

Thesis (Ph.D.(Language Education)) -- University of Limpopo, 2019 / The purpose of this study was to explore the challenges encountered by teachers in teaching reading to EFAL learners in rural schools. This is based on the fact that reading is a fundamental skill upon which all formal education depends. In view of this, a child who does not learn reading early enough is doom to underperform in their academic pursuits. Thus, any child who doesn’t learn to read early and well would not easily master the other literacy skills and is unlikely to ever perform well in school or in life. However, teaching reading to English first additional language learners comes with a lot of challenges. To this effect, Sentsho (2000) argues that many teachers are not perfect in that regard and this imperfectness impacts negatively on the outcomes which is on the learners (child). If the teachers are incapable of using basic structures correctly, or if his/her pronunciation is so bad that the words are incomprehensible, he/she would not be able to teach the spoken language competently. Among the main challenges identified in the literature review, the lack of teaching skills, remuneration, lack of resources, overcrowded classrooms are the major challenges encountered by the teachers. The study is located in the interpretive paradigm which sought to explore teachers’ experiences and their views. The experiences and the qualifications of teachers were taken into consideration during the empirical study when the interviews, seminar and the observations were conducted. Qualitative research approach was adopted in the study with the intentions of finding as much detail as possible using a case study design. Participants for this study were teachers who teach English first additional language at rural schools in the Seshego Circuit in Polokwane, Limpopo. The empirical investigation revealed that teachers did not have necessary skills and expertise to teach reading to EFAL learners. They knew less about the approaches to teaching reading and that reading was treated as a separate entity from speaking and writing. The conditions that they found themselves were appalling due to lack of motivation and support from the Department of Education, overcrowding in classrooms, lack of resources, socio-economic status etc. and how these factors impact negatively on the teaching of reading. Also important to note was the fact that the teachers did not receive any form of in-service training at their respective schools in relation to the teaching of reading. The investigation concluded that the teachers were qualified and had enough experience in teaching English but not reading per se.