Designing Engaging Learning Experiences in Programming

In this paper we describe work to investigate the creation of engaging programming learning experiences. Background research informed the design of four fieldwork studies to explore how programming tasks could be framed to motivate learners. Our empirical findings from these four field studies are summarized here, with a particular focus upon one – Whack a Mole – which compared the use of a physical interface with the use of a screen-based equivalent interface to obtain insights into what made for an engaging learning experience. Emotions reported by two sets of participant undergraduate students were analyzed, identifying the links between the emotions experienced during programming and their origin. Evidence was collected of the very positive emotions experienced by learners programming with a physical interface (Arduino) in comparison with a similar program developed using a screen-based equivalent interface. A follow-up study provided further evidence of the motivation of personalized design of programming tangible physical artefacts. Collating all the evidence led to the design of a set of ‘Learning Dimensions’ which may provide educators with insights to support key design decisions for the creation of engaging programming learning experiences

Associating Facial Expressions and Upper-Body Gestures with Learning Tasks for Enhancing Intelligent Tutoring Systems

Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of learner’s nonverbal behaviors involving hand-over-face gestures, head and eye movements and emotions via facial expressions during learning. The proposed computer vision-based behavior monitoring method uses a low-cost webcam and can easily be integrated with modern tutoring technologies. We investigate these behaviors in-depth over time in a classroom session of 40 minutes involving reading and problem-solving exercises. The exercises in the sessions are divided into three categories: an easy, medium and difficult topic within the context of undergraduate computer science. We found that there is a significant increase in head and eye movements as time progresses, as well as with the increase of difficulty level. We demonstrated that there is a considerable occurrence of hand-over-face gestures (on average 21.35%) during the 40 minutes session and is unexplored in the education domain. We propose a novel deep learning approach for automatic detection of hand-over-face gestures in images with a classification accuracy of 86.87%. There is a prominent increase in hand-over-face gestures when the difficulty level of the given exercise increases. The hand-over-face gestures occur more frequently during problem-solving (easy 23.79%, medium 19.84% and difficult 30.46%) exercises in comparison to reading (easy 16.20%, medium 20.06% and difficult 20.18%)

Observing response processes with eye tracking in international large-scale assessments: evidence from the OECD PIAAC assessment

This paper reports on a pilot study that used eye tracking techniques to make detailed observations of item response processes in the OECD Programme for the International Assessment of Adult Competencies (PIAAC). The lab-based study also recorded physiological responses using measures of pupil diameter and electrodermal activity. The study tested 14 adult respondents as they individually completed the PIAAC computer-based assessment. The eye tracking observations help to fill an ‘explanatory gap’ by providing data on variation in item response processes that are not captured by other sources of process data such as think aloud protocols or computer-generated log files. The data on fixations and saccades provided detailed information on test item response strategies, enabling profiling of respondent engagement and response processes associated with successful performance. Much of that activity does not include the use of the keyboard and mouse, and involves ‘off-screen’ use of pen and paper (and calculator) that are not captured by assessment log-files. In conclusion, this paper points toward an important application of eye tracking in large-scale assessments. This includes insights into response processes in new domains such as adaptive problem-solving that aim to identify individuals’ ability to select and combine resources from the digital and physical environment

Exploring the “impact” in Impact sourcing ventures: a sociology of space perspective

Using qualitative methods this paper explores the lived experience of individuals employed in impact sourcing ventures. In doing so, the paper attempts to understand “impact” from the point of view of beneficiaries. The paper, drawing on Georg Simmel’s work on the sociology of space, explores how space influences the lived experience of beneficiaries in ImS ventures. The findings highlight the various strategies adopted by beneficiaries to navigate the dialectical tensions experienced as a result of living and working in the new (ImS workplace) and the old (community) space. The paper also draws attention to the multifaceted nature of impact

Five Lenses on Team Tutor Challenges: A Multidisciplinary Approach

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs

Tune in to your emotions: a robust personalized affective music player

The emotional power of music is exploited in a personalized affective music player (AMP) that selects music for mood enhancement. A biosignal approach is used to measure listeners’ personal emotional reactions to their own music as input for affective user models. Regression and kernel density estimation are applied to model the physiological changes the music elicits. Using these models, personalized music selections based on an affective goal state can be made. The AMP was validated in real-world trials over the course of several weeks. Results show that our models can cope with noisy situations and handle large inter-individual differences in the music domain. The AMP augments music listening where its techniques enable automated affect guidance. Our approach provides valuable insights for affective computing and user modeling, for which the AMP is a suitable carrier application

Efficacy of a Mycotoxin Binder against Dietary Fumonisin, Deoxynivalenol, and Zearalenone in Rats

It was hypothesized that a mycotoxin binder, Grainsure E, would inhibit adverse effects of a mixture of fumonisin B1, deoxynivalenol, and zearalenone in rats. For 14 and 28 days, 8–10 Sprague–Dawley rats were fed control diet, Grainsure E (0.5%), toxins (7 μg fumonisin B1/g, 8 μg of deoxynivalenol/g and 0.2 μg of zearalenone/g), toxins (12 μg of fumonisin B1/g, 9 μg of deoxynivalenol/g, and 0.2 μg of zearalenone/g + Grainsure E), or pair-fed to control for food intake of toxin-fed rats. After 28 days, decreased body weight gain was prevented by Grainsure E in toxin-fed female rats, indicating partial protection against deoxynivalenol and fumonisin B1. Two effects of fumonisin B1 were partly prevented by Grainsure E in toxin-fed rats, increased plasma alanine transaminase (ALT) and urinary sphinganine/sphingosine, but sphinganine/sphingosine increase was not prevented in females at the latter time point. Grainsure E prevented some effects of fumonisin B1 and deoxynivalenol in rats

Determination of the LOQ in real-time PCR by receiver operating characteristic curve analysis: application to qPCR assays for Fusarium verticillioides and F. proliferatum

Real-time PCR (qPCR) is the principal technique for the quantification of pathogen biomass in host tissue, yet no generic methods exist for the determination of the limit of quantification (LOQ) and the limit of detection (LOD) in qPCR. We suggest using the Youden index in the context of the receiver operating characteristic (ROC) curve analysis for this purpose. The LOQ was defined as the amount of target DNA that maximizes the sum of sensitivity and specificity. The LOD was defined as the lowest amount of target DNA that was amplified with a false-negative rate below a given threshold. We applied this concept to qPCR assays for Fusarium verticillioides and Fusarium proliferatum DNA in maize kernels. Spiked matrix and field samples characterized by melting curve analysis of PCR products were used as the source of true positives and true negatives. On the basis of the analysis of sensitivity and specificity of the assays, we estimated the LOQ values as 0.11 pg of DNA for spiked matrix and 0.62 pg of DNA for field samples for F. verticillioides. The LOQ values for F. proliferatum were 0.03 pg for spiked matrix and 0.24 pg for field samples. The mean LOQ values correspond to approximately eight genomes for F. verticillioides and three genomes for F. proliferatum. We demonstrated that the ROC analysis concept, developed for qualitative diagnostics, can be used for the determination of performance parameters of quantitative PCR

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker