nils-herrmann/clean_scirepeval huggingface dataset:
Inclusion in early childhood education: pre service teachers voices

This study examined pre service teachers' understanding, attitudes, preparation and concerns regarding inclusion in early childhood education (ECE) in Zimbabwe. Entrenched within inclusive pedagogy, this descriptive study draws on a sample of 24 pre service teachers purposively selected from the largest teachers' college with the oldest specialized department for ECE in the country. Throughout the analysis, a constant comparative approach of organizing data with continual adjustment was used. Participants understood and held positive attitudes towards inclusion, but felt ill prepared for it and revealed social and cultural contextual barriers to its practice. Several strategies including the infusion of inclusive education training into regular teacher preparation courses, the development of advocacy expertise in pre service teachers, pooling resources, fostering positive attitudes among stakeholders and considering teachers' concerns in designing and implementing teacher preparation programmes would enhance inclusion in ECE in Zimbabwe. The study serves as a springboard for future studies on teacher preparation for inclusion.
Integration of digital technologies into play based pedagogy in Kuwaiti early childhood education: teachers' views, attitudes and aptitudes

Scholars in the field of early childhood education are still debating the inclusion of digital technologies in play based pedagogy and our understanding of digital play in early childhood education is still developing. This research paper examines early childhood education teachers' views, aptitudes and attitudes towards digital technologies in their personal lives and in the classroom practices in Kuwait. This is a quantitative study in which 195 teachers completed a questionnaire designed around the key themes of the investigation in an attempt to understand how teachers are positioning themselves in terms of a play based pedagogy and digital technologies. The key findings demonstrated that although the Kuwaiti teachers are competent users of digital technologies in their personal lives and the Kuwaiti classrooms have been digitalised to a large extent, the teachers are still hesitant in embedding these in their curriculum practices.
Learning in MOOCs: Motivations and self regulated learning in MOOCs
Venue: Internet High. Educ.

Massive open online courses (MOOCs) require individual learners to be able to self regulate their learning, determining when and how they engage. However, MOOCs attract a diverse range of learners, each with different motivations and prior experience. This study investigates the self regulated learning (SRL) learners apply in a MOOC, in particular focusing on how learners' motivations for taking a MOOC influence their behaviour and employment of SRL strategies. Following a quantitative investigation of the learning behaviours of 788 MOOC participants, follow up interviews were conducted with 32 learners. The study compares the narrative descriptions of behaviour between learners with self reported high and low SRL scores. Substantial differences were detected between the self described learning behaviours of these two groups in five of the sub processes examined. Learners' motivations and goals were found to shape how they conceptualised the purpose of the MOOC, which in turn affected their perception of the learning process.
Internet Addiction and Relationships with Insomnia, Anxiety, Depression, Stress and Self Esteem in University Students: A Cross Sectional Designed Study
Venue: PloS one

Internet addiction (IA) could be a major concern in university medical students aiming to develop into health professionals. The implications of this addiction as well as its association with sleep, mood disorders and self esteem can hinder their studies, impact their long term career goals and have wide and detrimental consequences for society as a whole. The objectives of this study were to: 1) Assess potential IA in university medical students, as well as factors associated with it; 2) Assess the relationships between potential IA, insomnia, depression, anxiety, stress and self esteem.  Our study was a cross sectional questionnaire based survey conducted among 600 students of three faculties: medicine, dentistry and pharmacy at Saint Joseph University. Four validated and reliable questionnaires were used: the Young Internet Addiction Test, the Insomnia Severity Index, the Depression Anxiety Stress Scales (DASS 21) and the Rosenberg Self Esteem Scale (RSES)  The average YIAT score was 30 18.474; Potential IA prevalence rate was 16.8% (95% confidence interval: 13.81 19.79% and it was significantly different between males and females (p value 0.003) with a higher prevalence in males (23.6% versus 13.9% Significant correlations were found between potential IA and insomnia, stress, anxiety, depression and self esteem (p value 0.001) ISI and DASS sub scores were higher and self esteem lower in students with potential IA.  Identifying students with potential IA is important because this addiction often coexists with other psychological problems. Therefore, interventions should include not only IA management but also associated psychosocial stressors such as insomnia, anxiety, depression, stress, and self esteem.
Exploring Writing Anxiety and Self Efficacy among EFL Graduate Students in Taiwan

This study investigates research writing anxiety and self efficacy beliefs among English as a Foreign Language (EFL) graduate students in engineering related fields. The relationship between the two writing affective constructs was examined and students' perspectives on research writing anxiety were also explored. A total of 218 survey responses from engineering graduate students at Taiwanese universities were analyzed, along with qualitative data from open ended questions and semi structured interviews. The findings show that while master's and doctoral students felt a similar moderate level of writing anxiety, senior doctoral students were more self efficacious about writing research papers in English than their junior counterparts. Overall, students with higher writing self efficacy felt less apprehensive. Additionally, among the individual variables, experience in writing for publication better predicted writing anxiety and self efficacy than students' self reported English proficiency and the number of writing courses taken. The qualitative findings indicated various sources of graduate level writing anxiety, including insufficient writing skills in English, time constraints, and fear of negative comments. Furthermore, composing different sections of a research paper provoked different levels of anxiety due to the variations in the rhetorical purposes and discourse structures of particular sections. Implications on dealing with research writing anxiety are also discussed.
Biomimetic coat enables the use of sonoporation to assist delivery of silica nanoparticle cargoes into human cells

Due to their biocompatibility and high adsorption properties, mesoporous silica nanoparticles (MSN) represent one of the most promising systems for drug delivery. Previous investigations have shown that both surface functionalization and external stimuli may act in a synergistic way to deliver drugs from nanoparticles. One such stimulus is underwater shock wave induced sonoporation, a physical method known to transiently permeabilize cell membranes. However, there are some concerns regarding the feasibility to apply shock waves in the presence of dense nanoparticles. In this work, bioinspired supramolecular MSN were prepared by self assembly of cationic liposomes with 200 nm MCM 41 type silica nanoparticles. The effects of the biomimetic coat on cargo stability, adherence to HEK 293 cells, and shock wave mediated delivery of plasmid deoxyribonucleic acid were addressed. Compared to bare MSN, structures displaying a lipid coat showed higher cargo retention. Adherence to cell surface was only achieved with
Emotion does not influence prefrontal cortex activity during a visual attention task. A functional near infrared spectroscopy study.

Research shows that positive and negative emotion can influence a range of cognitive processes as well as hemodynamic prefrontal cortex (PFC) activity. This study sought to investigate if PFC activity was influenced by positive and negative stimuli during mood induction as well as during a subsequent visual attention task. The International Affective Picture System was employed to induce affective states in participants before they completed a visual attention task. PFC hemodynamic activity was recorded using non invasive functional near infrared spectroscopy. Increased PFC activity was evident during the visual attention task compared to affective stimuli viewing. However, emotion did not influence PFC activity during affective stimuli viewing or completion of the visual attention task. Future research should take into account the role individual differences may play in mitigating any influence of emotion on PFC activity. Emotion; fNIRS; PFC; visual attention; mood; cognition
Things and Strings: Improving Place Name Disambiguation from Short Texts by Combining Entity Co Occurrence with Topic Modeling
Venue: EKAW

Place name disambiguation is the task of correctly identifying a place from a set of places sharing a common name. It contributes to tasks such as knowledge extraction, query answering, geographic information retrieval, and automatic tagging. Disambiguation quality relies on the ability to correctly identify and interpret contextual clues, complicating the task for short texts. Here we propose a novel approach to the disambiguation of place names from short texts that integrates two models: entity co occurrence and topic modeling. The first model uses Linked Data to identify related entities to improve disambiguation quality. The second model uses topic modeling to differentiate places based on the terms used to describe them. We evaluate our approach using a corpus of short texts, determine the suitable weight between models, and demonstrate that a combined model outperforms benchmark systems such as DBpedia Spotlight and Open Calais in terms of F1 score and Mean Reciprocal Rank.
Teaching culture(s) in English as a lingua franca in Asia: dilemma and solution

Before I start my talk, I would like to present to you two scenarios of English as a lingua franca (ELF) which I personally experienced. On 25 October 2013, the Executive Committee of Asia TEFL was held in Manila. Thirty four members from 17 Asian countries were present at the meeting. Among them were English native speakers, one teaching in South Korea and the other in Israel. The participants present spoke diverse mother tongues. Thus, English became a natural medium of communication. The second scenario is a TV program I recently watched. This program is for children to display their talents in singing, dancing, acting, etc. One of the performers is a five year old boy of mixed parentage. His mother is Chinese and his father, German. One of the TV hosts asked the boy a question: "What language is used to talk to your mum and dad?" The boy said "If I use Chinese, my dad cannot understand; If I use German, my mum cannot understand. When we talk together, we three have to use English." His mother further confirmed that English was the only means of communication between her husband and herself, and among the three members together. From these two scenarios, we can find that English is not only a shared communicative means among people with diverse mother tongues in an academic organization across Asian countries but also in a family of mixed marriage in China. The extensive use of ELF around the world enables people with diverse mother tongues to accomplish professional and business tasks so that the globalized professional and business activities can be accomplished without language barriers. It also enables peoples without a common communication means to exchange cultures so that the world culture can be enriched and further diversified
SPrank: Semantic Path Based Ranking for Top N Recommendations Using Linked Open Data
Venue: ACM Trans. Intell. Syst. Technol.

In most real world scenarios, the ultimate goal of recommender system applications is to suggest a short ranked list of items, namely top N recommendations, that will appeal to the end user. Often, the problem of computing top N recommendations is mainly tackled with a two step approach. The system focuses first on predicting the unknown ratings, which are eventually used to generate a ranked recommendation list. Actually, the top N recommendation task can be directly seen as a ranking problem where the main goal is not to accurately predict ratings but to directly find the best ranked list of items to recommend. In this article we present SPrank, a novel hybrid recommendation algorithm able to compute top N recommendations exploiting freely available knowledge in the Web of Data. In particular, we employ DBpedia, a well known encyclopedic knowledge base in the Linked Open Data cloud, to extract semantic path based features and to eventually compute top N recommendations in a learning to rank fashion. Experiments with three datasets related to different domains (books, music, and movies) prove the effectiveness of our approach compared to state of the art recommendation algorithms.
Query to Knowledge: Unsupervised Entity Extraction from Shopping Queries using Adaptor Grammars
Venue: SIGIR

Web search queries provide a surprisingly large amount of information, which can be potentially organized and converted into a knowledgebase. In this paper, we focus on the problem of automatically identifying brand and product entities from a large collection of web queries in online shopping domain. We propose an unsupervised approach based on adaptor grammars that does not require any human annotation efforts nor rely on any external resources. To reduce the noise and normalize the query patterns, we introduce a query standardization step, which groups multiple search patterns and word orderings together into their most frequent ones. We present three different sets of grammar rules used to infer query structures and extract brand and product entities. To give an objective assessment of the performance of our approach, we conduct experiments on a large collection of online shopping queries and intrinsically evaluate the knowledgebase generated by our method qualitatively and quantitatively. In addition, we also evaluate our framework on extrinsic tasks on query tagging and chunking. Our empirical studies show that the knowledgebase discovered by our approach is highly accurate, has good coverage and significantly improves the performance on the external tasks.
Investigation of the seismic response of high rise buildings supported on tension resistant elastomeric isolation bearings

In many applications of seismic isolation, such as in high rise construction, lightweight construction, and structures with large height to width aspect ratios, significant tension forces can develop in bearings, raising concerns about the possible rupture of elastomeric bearings and the uplift of sliding bearings. In this paper, a novel tension resistant lead plug rubber bearing (TLRB) with improved tension resisting capabilities is developed and experimentally and numerically assessed. This TLRB consists of a common lead plug rubber bearing (LRB) and several helical springs. After describing the theory underlying the behavior of the TLRB, the mechanical properties of reduced scale prototype bearings are investigated through extensive horizontal and vertical loading tests. The test results indicate that TLRBs can improve the shear stiffness and tension resistance capacity even under significant tensile loads. A series of shaking table tests on scaled models of high rise buildings with different aspect ratios were conducted to investigate the dynamic performance of the TLRB and the seismic responses of base isolated high rise buildings. Three different cases were considered in the shaking table tests: a fixed base condition and the use of TLRB and LRB isolation systems. The results of the shaking table test show that (a) base isolated systems are effective in reducing the structural responses of high rise buildings; (b) an isolated structure's aspect ratio is an important factor influencing its dynamic response; (c) TLRBs can endure large tensile stresses and avoid rupture on rubber bearings under strong earthquakes; and (d) the experimental and numerical results of the responses of the models show good agreement.
Expressive Collaborative Music Performance via Machine Learning

To my parents and my girlfriend.  Techniques of Artificial Intelligence and Human Computer Interaction have empowered computer music systems with the ability to perform with humans via a wide spectrum of applications. However, musical interaction between humans and machines is still far less musical than the interaction between humans since most systems lack any representation or capability of musical expression. This thesis contributes various techniques, especially machine learning algorithms, to create artificial musicians that perform expressively and collaboratively with humans. The current system focuses on three aspects of expression in human computer collaborative performance: 1) expressive timing and dynamics, 2) basic improvisation techniques, and 3) facial and body gestures. Timing and dynamics are the two most fundamental aspects of musical expression and also the main focus of this thesis. We model the expression of different musicians as co evolving time series. Based on this representation, we develop a set of algorithms, including a sophisticated spectral learning method, to discover regularities of expressive musical interaction from rehearsals. Given a learned model, an artificial performer generates its own musical expression by interacting with a human performer given a pre defined score. The results show that, with a small number of rehearsals, we can successfully apply machine learning to generate more expressive and human like collaborative performance than the baseline automatic accompaniment algorithm. This is the first application of spectral learning in the field of music. Besides expressive timing and dynamics, we consider some basic improvisation techniques where musicians have the freedom to interpret pitches and rhythms. We developed a model that trains a different set of parameters for each individual measure and focus on the prediction of the number of chords and the number of notes per chord. Given the model prediction, an improvised score is decoded using nearest neighbor search, which selects the training example whose parameters are closest to the estimation. Our result shows that our model generates more musical, interactive, and natural collaborative improvisation than a reasonable baseline based on mean estimation. Although not conventionally considered to be " music, " body and facial movements are also important aspects of musical expression. We study body and facial expressions using a humanoid saxophonist robot. We contribute the first algorithm to enable a robot to perform an accompaniment for a musician and react to human performance with gestural and facial expression. The current system uses rule based performance motion mapping and separates robot motions into three groups: finger motions,
Bibliogifts in LibGen? A study of a text sharing platform driven by biblioleaks and crowdsourcing
Venue: J. Assoc. Inf. Sci. Technol.

Research articles disseminate the knowledge produced by the scientific community. Access to this literature is crucial for researchers and the general public. Apparently, "bibliogifts" are available online for free from text sharing platforms. However, little is known about such platforms. What is the size of the underlying digital libraries? What are the topics covered? Where do these documents originally come from? This article reports on a study of the Library Genesis platform (LibGen) The 25 million documents (42 terabytes) it hosts and distributes for free are mostly research articles, textbooks, and books in English. The article collection stems from isolated, but massive, article uploads (71% in line with a "biblioleaks" scenario, as well as from daily crowdsourcing (29% by worldwide users of platforms such as Reddit Scholar and Sci Hub. By relating the DOIs registered at CrossRef and those cached at LibGen, this study reveals that 36% of all DOI articles are available for free at LibGen. This figure is even higher (68% for three major publishers: Elsevier, Springer, and Wiley. More research is needed to understand to what extent researchers and the general public have recourse to such text sharing platforms and why.
Adaptive fuzzy fault tolerant tracking control for a class of uncertain switched nonlinear systems with output constraints
Venue: J. Frankl. Inst.

This paper studies the adaptive fuzzy fault tolerant tracking control problem for a class of switched multi input multi output (MIMO) nonlinear systems with output constraints under arbitrary switchings. The actuator faults under study consist of unknown stuck and loss of effectiveness. In the design procedure, the unknown control signals are approximated directly by fuzzy logic systems. To prevent constraints violation, a tan type barrier Lyapunov function is incorporated into the Lyapunov function design. Based on the idea of estimating the bound on switching parameters, a novel adaptive fuzzy fault tolerant tracking control technique for the problem studied is set up by exploiting the common Lyapunov function method and backstepping. It is shown that under the proposed control law and adaption rules, all the signals remain bounded and the system output tracking error can be guaranteed to exponentially converge to a neighborhood of origin, while the constraints on the system output will not be violated during operation. Finally, simulation results are presented to show the effectiveness of the proposed approaches.
Pre registration in social psychology A discussion and suggested template

Pre registration of studies before they are conducted has recently become more feasible for researchers, and is encouraged by an increasing number of journals. However, because the practice of pre registration is relatively new to psychological science, specific guidelines for the content of registrations are still in a formative stage. After giving a brief history of pre registration in medical and psychological research, we outline two different models that can be applied reviewed and unreviewed pre registration and discuss the advantages of each model to science as a whole and to the individual scientist, as well as some of their drawbacks and limitations. Finally, we present and justify a proposed standard template that can facilitate pre registration. Researchers can use the template before and during the editorial process to meet article requirements and enhance the robustness of their scholarly efforts.