A longitudinal evaluation of the acceptability and impact of a diet diary app for older adults with age-related macular degeneration

Ongoing advances in technology are increasing the scope for enhancing and supporting older adults’ daily living. The digital divide between older and younger adults raises concerns, however, about the suitability of technological solutions for older adults, especially for those with impairments. Taking older adults with Age-Related Macular Degeneration (AMD) as a case study, we used user-centred and participatory design approaches to develop an assistive mobile app for self-monitoring their intake of food [12,13]. In this paper we report on findings of a longitudinal field evaluation of our app that was conducted to investigate how it was received and adopted by older adults with AMD and its impact on their lives. Demonstrating the benefit of applying inclusive design methods for technology for older adults, our findings reveal how the use of the app raises participants’ awareness and facilitates self-monitoring of diet, encourages positive (diet) behaviour change, and encourages learning.

Supporting learners’ agentic engagement with feedback:a systematic review and a taxonomy of recipience processes

Much has been written in the educational psychology literature about effective feedback and how to deliver it. However, it is equally important to understand how learners actively receive, engage with, and implement feedback. This article reports a systematic review of the research evidence pertaining to this issue. Through an analysis of 195 outputs published between 1985 and early 2014, we identified various factors that have been proposed to influence the likelihood of feedback being used. Furthermore, we identified diverse interventions with the common aim of supporting and promoting learners' agentic engagement with feedback processes. We outline the various components used in these interventions, and the reports of their successes and limitations. Moreover we propose a novel taxonomy of four recipience processes targeted by these interventions. This review and taxonomy provide a theoretical basis for conceptualizing learners' responsibility within feedback dialogues and for guiding the strategic design and evaluation of interventions. Receiving feedback on one's skills and understanding is an invaluable part of the learning process, benefiting learners far more than does simply receiving praise or punishment (Black & Wiliam, 1998 Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5, 7–74. doi:10.1080/0969595980050102[Taylor & Francis Online]; Hattie & Timperley, 2007 Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112. doi:10.3102/003465430298487[CrossRef], [Web of Science ®]). Inevitably, the benefits of receiving feedback are not uniform across all circumstances, and so it is imperative to understand how these gains can be maximized. There is increasing consensus that a critical determinant of feedback effectiveness is the quality of learners' engagement with, and use of, the feedback they receive. However, studies investigating this engagement are underrepresented in academic research (Bounds et al., 2013 Bounds, R., Bush, C., Aghera, A., Rodriguez, N., Stansfield, R. B., & Santeen, S. A. (2013). Emergency medicine residents' self-assessments play a critical role when receiving feedback. Academic Emergency Medicine, 20, 1055–1061. doi:10.1111/acem.12231[CrossRef], [PubMed], [Web of Science ®]), which leaves a “blind spot” in our understanding (Burke, 2009 Burke, D. (2009). Strategies for using feedback students bring to higher education. Assessment & Evaluation in Higher Education, 34, 41–50. doi:10.1080/02602930801895711[Taylor & Francis Online], [Web of Science ®]). With this blind spot in mind, the present work sets out to systematically map the research literature concerning learners' proactive recipience of feedback. We use the term “proactive recipience” here to connote a state or activity of engaging actively with feedback processes, thus emphasizing the fundamental contribution and responsibility of the learner (Winstone, Nash, Rowntree, & Parker, in press Winstone, N. E., Nash, R. A., Rowntree, J., & Parker, M. (in press). ‘It'd be useful, but I wouldn't use it’: Barriers to university students' feedback seeking and recipience. Studies in Higher Education. doi: 10.1080/03075079.2015.1130032[Taylor & Francis Online]). In other words, just as Reeve and Tseng (2011 Reeve, J., & Tseng, M. (2011). Agency as a fourth aspect of student engagement during learning activities. Contemporary Educational Psychology, 36, 257–267. doi:10.1016/j.cedpsych.2011.05.002[CrossRef], [Web of Science ®]) defined “agentic engagement” as a “student's constructive contribution into the flow of the instruction they receive” (p. 258), likewise proactive recipience is a form of agentic engagement that involves the learner sharing responsibility for making feedback processes effective.

PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.

Firms’ innovation objectives and knowledge acquisition strategies:a comparative analysis

External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.

Mindmapping as an adult learning notetaking strategy to increase the encoding of information in a corporate training course

A study was conducted to investigate the effectiveness, as measured by performance on course posttests, of mindmapping versus traditional notetaking in a corporate training class. The purpose of this study was to increase knowledge concerning the effectiveness of mindmapping as an information encoding tool to enhance the effectiveness of learning. Corporations invest billions of dollars, annually, in training programs. Given this increased demand for effective and efficient workplace learning, continual reliance on traditional notetaking is questionable for the high-speed and continual learning required on workers.^ An experimental, posttest-only control group design was used to test the following hypotheses: (1) there is no significant difference in posttest scores on an achievement test, administered immediately after the course, between adult learners using mindmapping versus traditional notetaking methods in a training lecture, and (2) there is no significant difference in posttest scores on an achievement test, administered 30 days after the course, between adult learners using mindmapping versus traditional notetaking methods in a training lecture. After a 1.5 hour instruction on mindmapping, the treatment group used mindmapping throughout the course. The control group used traditional notetaking. T-tests were used to determine if there were significant differences between mean posttest scores between the two groups. In addition, an attitudinal survey, brain hemisphere dominance survey, course dynamics observations, and course evaluations were used to investigate preference for mindmapping, its perceived effect on test performance, and the effectiveness of mindmapping instruction.^ This study's principal finding was that although the mindmapping group did not perform significantly higher on posttests administered immediately and 30 days after the course, than the traditional notetaking group, the mindmapping group did score higher on both posttests and reported higher ratings of the course on every evaluation criteria. Lower educated, right brain dominant learners reported a significantly positive learning experience. These results suggest that mindmapping enhances and reinforces the preconditions of learning. Recommendations for future study are provided. ^

Theological reflection at work: A phenomenological study of learning processes

Using the learning descriptions of graduates of a graduate ministry program, the mechanisms of interactions between the knowledge facets in learning processes were explored and described. The intent of the study was to explore how explicit, implicit, and emancipatory knowledge facets interacted in the learning processes at or about work. The study provided empirical research on Yang's (2003) holistic learning theory. ^ A phenomenological research design was used to explore the essence of knowledge facet interactions. I achieved epoche through the disclosure of assumptions and a written self-experience to bracket biases. A criterion based, stratified sampling strategy was used to identify participants. The sample was stratified by graduation date. The sample consisted of 11 participants and was composed primarily of married (n = 9), white, non-Hispanic (n = 10), females (n = 9), who were Roman Catholic (n = 9). Professionally, the majority of the group were teachers or professors (n = 5). ^ A semi-structured interview guide with scheduled and unscheduled probes was used. Each approximately 1-hour long interview was digitally recorded and transcribed. The transcripts were coded using a priori codes from holistic learning theory and one emergent code. The coded data were analyzed by identifying patterns, similarities, and differences under each code and then between codes. Steps to increase the trustworthiness of the study included member checks, coding checks, and thick descriptions of the data. ^ Five themes were discovered including (a) the difficulty in describing interactions between knowledge facets; (b) actual mechanisms of interactions between knowledge facets; (c) knowledge facets initiating learning and dominating learning processes; (d) the dangers of one-dimensional learning or using only one knowledge facet to learn; and (e) the role of community in learning. The interpretation confirmed, extended, and challenged holistic learning theory. Mechanisms of interaction included knowledge facets expressing, informing, changing, and guiding one another. Implications included the need for a more complex model of learning and the value of seeing spirituality in the learning process. The study raised questions for future research including exploring learning processes with people from non-Christian faith traditions or other academic disciplines and the role of spiritual identity in learning. ^

Borinquen, la tierra de Belen: Participatory Action Research and Transformational Theory in the Urban Chicago Puerto Rican Experience: A Critical Analysis

This paper analyzes how José Lopéz’s participatory action research and transformational learning theory addresses the oppressed Puerto Rican experience. The paper examines the historical experience of colonialism, explains these two theories, and explores Lopéz’s adult education work in the Puerto Rican community using participatory action research and transformational learning.

Increasing Informal Learning Opportunities for Teachers in the School Setting

This paper comprehensively defines how to implement informal learning strategies into the classroom setting using Marsick and Watkins’s Incidental Learning Model (2001). Existing barriers that stand between educators and informal learning in the school setting are explained. Implications for removing said inhibitors while increasing learning are explicated.

Waking the sleeping giant: Beliefs of Brazilian and *American teachers concerning liberation curriculum

The school curriculum is a matter mandated by the educational system rather than determined by the school stakeholders of a community, as Freire (1993) suggests. At the present time, one significant vision of school is challenging the current order of curriculum practice. It focuses on school as a liberating agency grounded on the belief that the abilities to access information and to think critically about it will educate an individual capable of making independent decisions. This dissertation investigates teacher's beliefs concerning curriculum. It was assumed that there is a discrepancy between what has been the position proposed by critical theorists including Freire (1998a, 1993); Apple (1979); Giroux (1998), and the position on curriculum which school systems are typically advancing. ^ There were four purposes of this study. The major purpose of this study was to determine whether or not Brazilian and American Teachers believe that a school curriculum based on Freirean principles could be implemented in the schools in which they worked. Also, this study sought to determine the differences found between teachers' beliefs in the Brazilian and American contexts. Another purpose was to determine how Brazilian and American teachers justify their beliefs and actions when these may represent conflicting values. Finally, this study sought to determine if these teachers believe that the curriculum is in need of change or if they accept the current curriculum as adequate. This study consisted of quantitative and qualitative data collection through multiple methods involving surveys and interviews. The study involved 171 teachers (88 Brazilian and 83 American) from multiple settings with the majority working for public systems. Overall, it seems that Brazilian and American teachers believe that a curriculum based on Freirean principles of education can be implemented in their schools, if ongoing education is provided. The majority of Brazilian teachers believe a curriculum change is necessary while half of the American teachers believe a curriculum change is needed and the other half seems to believe curriculum is adequate. Teachers explain that it is hard to implement a curriculum they believe to be most appropriate for students because the current curriculum is mandated by the school system or by national guidelines. The majority of Brazilian teachers and those American teachers who believed a curriculum change is necessary explained their rationale for change in terms of social justice, problem-solving, collective work, student-centered and context-based curriculum. American teachers, who believed that the curriculum is adequate, explained that they are satisfied with their student's achievements. They stated that their students are doing well on tests and are learning what is required. ^

Commitment language as a predictor of alcohol and marijuana use outcomes among adolescents in school -based group treatment

Despite widespread recognition of the problem of adolescent alcohol and other drug (AOD) abuse, research on its most common treatment modality, group work, is lacking. This research gap is alarming given that outcomes range from positive to potentially iatrogenic. This study sought to identify change mechanisms and/or treatment factors that are observable within group treatment sessions and that may predict AOD use outcomes. This NIH (F31 DA 020233-01A1) study evaluated 108, 10-19 year olds and the 19 school-based treatment groups to which they were previously assigned (R01 AA10246; PI: Wagner). Associations between motivational interviewing (MI) based change talk variables, group leader MI skills, and alcohol and marijuana use outcomes up to 12-months following treatment were evaluated. Treatment session audio recordings and transcripts (1R21AA015679-01; PI: Macgowan) were coded using a new discourse analysis coding scheme for measuring group member change talk (Amrhein, 2003). Therapist MI skills were similarly measured using the Motivational Interviewing Treatment Integrity instrument. Group member responses to commitment predicted group marijuana use at the 1-month follow up. Also, group leader empathy was significantly associated with group commitment for marijuana use at the middle and ending stages of treatment. Both of the above process measures were applied in a group setting for the first time. Building upon MI and social learning theory principles, group commitment and group member responses to commitment are new observable, in-session, process constructs that may predict positive and negative adolescent group treatment outcomes. These constructs, as well as the discourse analysis method and instruments used to measure them, raise many possibilities for future group work process research and practice.

The Relation Between Civic Education and Political Attitudes and Behavior

It is generally assumed that civic education efforts will have a positive effect on the political attitudes and behaviors of adolescents and young adults. There is less agreement, however, on the most effective forms of civic education. In the present study, we distinguish between formal civic education, an open classroom climate and active learning strategies, and we explore their effect on political interest, efficacy, trust and participation. To analyze these effects, we rely on the results of a two-year panel study among late adolescents in Belgium. The results indicate that formal civic education (classroom instruction) and active learning strategies (school council membership and, to a lesser extent, group projects) are effective in shaping political attitudes and behavior. An open classroom climate, on the other hand, has an effect on political trust. We conclude that there is no reason to privilege specific forms of civic education, as each form contributes to different relevant political attitudes and behaviors.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.

Learning from Geometry

Subspaces and manifolds are two powerful models for high dimensional signals. Subspaces model linear correlation and are a good fit to signals generated by physical systems, such as frontal images of human faces and multiple sources impinging at an antenna array. Manifolds model sources that are not linearly correlated, but where signals are determined by a small number of parameters. Examples are images of human faces under different poses or expressions, and handwritten digits with varying styles. However, there will always be some degree of model mismatch between the subspace or manifold model and the true statistics of the source. This dissertation exploits subspace and manifold models as prior information in various signal processing and machine learning tasks.

A near-low-rank Gaussian mixture model measures proximity to a union of linear or affine subspaces. This simple model can effectively capture the signal distribution when each class is near a subspace. This dissertation studies how the pairwise geometry between these subspaces affects classification performance. When model mismatch is vanishingly small, the probability of misclassification is determined by the product of the sines of the principal angles between subspaces. When the model mismatch is more significant, the probability of misclassification is determined by the sum of the squares of the sines of the principal angles. Reliability of classification is derived in terms of the distribution of signal energy across principal vectors. Larger principal angles lead to smaller classification error, motivating a linear transform that optimizes principal angles. This linear transformation, termed TRAIT, also preserves some specific features in each class, being complementary to a recently developed Low Rank Transform (LRT). Moreover, when the model mismatch is more significant, TRAIT shows superior performance compared to LRT.

The manifold model enforces a constraint on the freedom of data variation. Learning features that are robust to data variation is very important, especially when the size of the training set is small. A learning machine with large numbers of parameters, e.g., deep neural network, can well describe a very complicated data distribution. However, it is also more likely to be sensitive to small perturbations of the data, and to suffer from suffer from degraded performance when generalizing to unseen (test) data.

From the perspective of complexity of function classes, such a learning machine has a huge capacity (complexity), which tends to overfit. The manifold model provides us with a way of regularizing the learning machine, so as to reduce the generalization error, therefore mitigate overfiting. Two different overfiting-preventing approaches are proposed, one from the perspective of data variation, the other from capacity/complexity control. In the first approach, the learning machine is encouraged to make decisions that vary smoothly for data points in local neighborhoods on the manifold. In the second approach, a graph adjacency matrix is derived for the manifold, and the learned features are encouraged to be aligned with the principal components of this adjacency matrix. Experimental results on benchmark datasets are demonstrated, showing an obvious advantage of the proposed approaches when the training set is small.

Stochastic optimization makes it possible to track a slowly varying subspace underlying streaming data. By approximating local neighborhoods using affine subspaces, a slowly varying manifold can be efficiently tracked as well, even with corrupted and noisy data. The more the local neighborhoods, the better the approximation, but the higher the computational complexity. A multiscale approximation scheme is proposed, where the local approximating subspaces are organized in a tree structure. Splitting and merging of the tree nodes then allows efficient control of the number of neighbourhoods. Deviation (of each datum) from the learned model is estimated, yielding a series of statistics for anomaly detection. This framework extends the classical {\em changepoint detection} technique, which only works for one dimensional signals. Simulations and experiments highlight the robustness and efficacy of the proposed approach in detecting an abrupt change in an otherwise slowly varying low-dimensional manifold.

Sequence and Structural Determinants of Specificity Differences between Paralogous Transcription Factors

Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.

The Role of Social Cognition and Person Perception in Economic Social Decision-Making

Social decision-making is often complex, requiring the decision-maker to make social inferences about another person in addition to engaging traditional decision-making processes. However, until recently, much research in neuroeconomics and behavioral economics has examined social decision-making while failing to take into account the importance of the social context and social cognitive processes that are engaged when viewing another person. Using social psychological theory to guide our hypotheses, four research studies investigate the role of social cognition and person perception in guiding economic decisions made in social contexts. The first study (Chapter 2) demonstrates that only specific types of social information engage brain regions implicated in social cognition and hinder learning in social contexts. Study 2 (Chapter 3) extends these findings and examines contexts in which this social information is used to generalize across contexts to form predictions about another person’s behavior. Study 3 (Chapter 4) demonstrates that under certain contexts these social cognitive processes may be withheld in order to more effectively complete the task at hand. Last, Study 4 (Chapter 5) examines how this knowledge of social cognitive processing can be used to change behavior in a prosocial group context. Taken together, these studies add to the growing body of literature examining decision-making in social contexts and highlight the importance of social cognitive processing in guiding these decisions. Although social cognitive processing typically facilitates social interactions, these processes may alter economic decision-making in social contexts.