Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategy Use and Language Performance by Second Language Learners in Nigeria

It is commonly believed that Nigerian students perform very poorly in the English language. Many reasons adduced to be the causative variables for students’ poor performance in the English language are located away from the students themselves. What the above scenario portends is that no effort has been made to find out the strategies which the students themselves use in their efforts to learn the English language; it also implies that no effort has been made to find out the relationship between such strategies and the level of students’ performance in the target language. The problem which this study addressed was not only to evaluate the language learning strategies which the sampled study population use in their efforts to learn English, but also to determine the extent to which their mean achievement scores in English depend on their use of various language learning strategies. The study was carried out using a descriptive survey research design. Its population consisted of Senior Secondary School (SSS) form II students in three states of south-eastern Nigeria. Random sampling technique was used to select a total of one thousand, four hundred and one (1401: 747 = males, 654 = females) students used for the study. Two sets of instrument were used to collect data for the investigation: appraisal instrument (cloze test), and questionnaire. Two research questions and corresponding two null hypotheses were formulated to guide the study. Results of the study revealed that 1) the greatest proportion of the Igbo learners of English in SSS II (84.3%) made use of socio-affective language learning strategy, while cognitive strategy had the lowest proportion of users (50.9%); 2) there was a significant difference, in the English language performance, between the users and non-users of the various language learning strategies.
Little Machiavellians: Deception in Early Childhood

The analyses in this dissertation were designed to identify 1) whether there is an age effect among three-, four-, and five-year-old preschool children for false-belief understanding, deceptive ability, and deception detection ability, 2) whether there is a gender effect among preschool children for false-belief understanding, deceptive ability, and deception detection ability, 3) whether there is a relationship between false-belief understanding, deceptive ability, and deception detection ability in preschool children, and 4) whether there is a relationship between peer acceptance and false-belief understanding, deceptive ability, and deception detection ability among preschool children. Participants were 78 (34 male, 44 female) preschool children of mixed ethnicity who were between three to five years of age. All subjects completed four tasks that assessed false-belief understanding, deceptive ability, deception detection ability, and peer acceptance. Results from the four-way repeated measures mixed-model analysis of variance (2 Gender x 3 Age x 2 False-Belief Understanding x 2 Deception) suggest that there is a task effect, age effect, gender effect, and false-belief understanding effect for deception among preschool children. Children received significantly higher scores on the deception detection ability task than they did on the deceptive ability task. This indicates that young children find deception detection to be easier than deceptive ability. In addition, this also provides evidence that deceptive ability and that deception detection are two separate constructs. This is further supported by the principal components analysis, which extracted two separate components for deception intelligence. In addition, three-year-old children perform significantly lower than fourand five-year-old
Study on the Effects of Gloss Type on Chinese EFL Learners’ Incidental Vocabulary Acquisition

Gloss is a common practice in reading materials. This study aims to explore the effects of gloss type on Chinese EFL learners’ English incidental vocabulary acquisition through reading. The experimental results indicate that: (1) multiple-choice glosses outperformed single glosses in incidental vocabulary gain and retention during reading; (2) compared with single glosses, multi-choice glosses were more conductive to vocabulary production.
Encouraging students to ‘think as biologists’: independent field-based projects and peer assessment as a deep learning strategy

Based on criteria of contextual factors that encourage a deep approach to learning, an independent field-based activity for students of behavioural ecology was created. The project was designed in such a way as to allow responsible choice in the method and content (animal species) of study, involved posing questions and problem solving, and modelled the process of conducting and publishing the results of research. Results from collection of quantitative data on students’ perceptions suggested that the learning context created through the activity encouraged problem solving, provided appropriate feedback, had clear aims and goals and was constructed in a fashion that allowed flexibility and responsible choice. Students’ perceptions of their orientation to learning were consistent with attributes of a deep-learning approach. Students agreed that the project encouraged learning for understanding, engagement, confidence and self-efficacy, and personal growth. To address the problems of obtaining insufficient feedback during the writing of a scientific manuscript based on the project, a peer assessment component was introduced modelling the scientific publication process. Providing feedback to peers helped students critically reflect and identify the important attributes of a paper suitable for publication. Receiving written feedback from peers also allowed reflection and modification of writing and the interpretation of findings.
An Experiment on Supporting Children's English Vocabulary Learning in Multimedia Context

Learning in context is an important component of second language (L2) vocabulary teaching and learning. However, young children may encounter some difficulties in dealing with the context. Hence learning support should be included to facilitate learning. The present study examined the effects of two types of learning support on Chinese children's (7 years of age) learning of English words: sentence-level translation (SLT) and target warming-up (TW). The results indicated that learning L2 vocabulary in an animation-based context without any learning support was inefficient for the young beginners. SLT and TW were both effective in facilitating L2 learning in a multimedia context. These findings have important implications for L2 vocabulary teaching and the design of effective multimedia L2 teaching tools.
The effect of dictoglass as a language task in enchacing students' grammatical competence in SK Felda Ulu Tebrau

This current study investigates the effect of dictogloss as a language task in enhancing students grammatical competence. The main focus of this study was to seek whether dictogloss task can help to improve students knowledge on simple past tense. A comparison between the dictogloss and the traditional method were also done to identify the most effective method in students acquiring grammar. This study also seeks to answer what are the students attitudes towards the dictogloss technique. This study was conducted in a primary school which involved 30 Year 5 students from two different classes and they were 5 Al Farabi and 5 Al Jazari. The treatment was administrated for 12 weeks which consists of grammar teaching using the traditional method and the dictogloss technique for one hour each week. A quasi-experimental design was used to measure the effectiveness of dictogloss in enhancing students grammatical competence. Mean and standard deviation were performed on the data to answer the research questions. The results of the data analysis indicated that students from the experimental group performed better after being exposed to the dictogloss technique compared to the students from the control group. This was seen in terms of the marks that were obtained in the posttest. Learners also have positive attitudes towards the dictogloss technique and this was seen through the analysis of questionnaire. Implication for future research and classroom practice was discussed. Some recommendations for future research were also indicated.
The Art of Problem Posing

Contents: Introduction. Two Problem Posing Perspectives: Accepting and Challenging. The First Phase of Problem Posing: Accepting. The Second Phase of Problem Posing: "What-If-Not". The "What-If-Not" Strategy in Action. Some Natural Links Between Problem Posing and Problem Solving. Writing for Journals of Editorial Boards: Student as Author and Critic. Conclusion.
The Academic Librarian: Buying Into, Playing Out, and Resisting the Teacher Role in Higher Education

This article reports the findings of a small-scale study in a UK university. The research investigated how academic librarians experienced the processes of becoming a teacher. As more librarians are drawn into a teaching role, understanding these developments becomes crucial. A narrative approach revealed the challenges faced as they participated in a program of teacher education. Institutional agendas and a diverse student population complicated these processes. This produced a complex interplay between identity and pedagogy, resulting in a lack of legitimacy in the teacher role. This has implications for the way in which academic librarians are supported in such transitions.
MIMO Communications - Motivation and a Practical Realization

Abstract Under rich scattering environment, Multiple Input Multiple Output (MIMO) systems have the potential to achieve capacities inconceivable by Single Input Single Output (SISO) systems. This makes it one of the most exciting developments to have occurred in wireless communications. Within a short duration, it has matured from a reasearch topic into a technology to find a place in upcoming wireless communication standards. This paper focuses on the spatial multiplexing aspects of MIMO. Starting from AWGN channels, we bring out how fading, which is typically an undesirable phenomenon, can be gainfully exploited to attain large capacities under MIMO configuration. We first briefly discuss some MIMO architectures initially designed to realize a large portion of the theoretical MIMO capacity, namely V-BLAST (Vertical Bell Labs Layered Space-Time) and D-BLAST (Diagonal BLAST), and then describe briefly the conventional V-BLAST receivers and a receiver that attains near optimal performance while keeping the complexity low. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and MIMO is introduced as a simple method to apply MIMO communication in a delay spread environment. Taking the example of Wireless Local Area Network (WLAN) standard IEEE 802.11n , we see how the research developments have been incorporated in a practical system.
A Comprehensive Case Study: An Examination of Machine Learning and Connectionist Algorithms

This case study examines the performance of 16 well-known and widely-used inductive learning algorithms on a comprehensive collection (102) of commonly available learning problems. It is distinguished from other, similar studies by the number of learning models used, the number of problems examined, and the rigor with which it has been conducted. The results of future case studies, which are done with the method and tools presented here, with learning problems used in this study, and with the same rigor, should be readily reproducible and directly comparable to the results of this study. An extensive set of tools is offered.
Generative perspectives on language acquisition : empirical findings, theoretical considerations, and crosslinguistic comparisons

1. Tables and Figures 2. Abbreviations 3. Contributors 4. Introduction (by Clahsen, Harald) 5. The Optional-Infinitive Stage in Child English: Evidence from Negation (by Harris, Tony) 6. Towards a Structure-Building Model of Acquisition (by Radford, Andrew) 7. The Underspecification of Functional Categories in Early Grammar (by Hyams, Nina) 8. Lexical Learning in Early Syntactic Development (by Clahsen, Harald) 9. Strong Continuity, Parameter Setting and the Trigger Hierarchy: On the Acquisition of the DP in Bernese Swiss German and High German (by Penner, Zvi) 10. Subject-Verb and Object-Verb Agreement in Early Basque (by Meisel, Jurgen M.) 11. Acquisition of Italian Interrogatives (by Guasti, Maria Teresa) 12. Root Infinitives, Clitics and Truncated Structures (by Haegeman, Liliane) 13. On the Acquisition of Subject and Object Clitics in French (by Hamann, Cornelia) 14. Clitics in L2 French (by White, Lydia) 15. The Initial Hypothesis of Syntax: A Minimalist Perspective on Language Acquisition and Attrition (by Platzack, Christer) 16. The Role of Merger Theory and Formal Features in Acquisition (by Roeper, Thomas) 17. How, Hang on a Minute: Some reflections on emerging orthodoxies (by Atkinson, Martin) 18. Index of Names 19. Index of Subjects
Facilitating Computer Conferencing: Recommendations from the Field.

Introduction Over the past few decades, several technologies have emerged that can be used in education, more specifically in distance learning: audio-, video-, and computer conferences; audiographics; CD-ROM, and other forms of computer-based instruction. When using most of these more sophisticated technologies, it becomes essential that an adequate infrastructure be constructed and high-quality technical support be made available when students and instructors need it. An overarching assumption here is that when designing instruction the use of technology is secondary to well-developed learning objectives and instructional plans. A set of guidelines may help design the learning environment. A few are listed here as examples of designing (especially distance) learning, but not as a comprehensive list:
Divine commands, authority, and cult. Imperative dedications to the Egyptian gods

This article presents the dedications made to the Egyptian deities “in accordance with divine command” in the eastern Mediterranean during the Hellenistic and Roman periods. The gods of Egypt exhorted and, if disobeyed, demanded from their adherents the performance of specific actions. As it is demonstrated by “imperative dedications” this communication between gods and worshippers was disclosed in public. First, the article examines the imperative expressions in use, the syntax and style of dedicatory language, and proposes a typology of “imperative dedications” in the framework of Isiac cults. Moreover, it is argued that imperatives constituted a means for the promotion of Isiac cults; most often, the Egyptian gods requested the execution of ritual acts, which either improved and embellished already-founded Isiac cults, or advanced the introduction of Isiac divinities in the cities of the Graeco-Roman world. Finally, it is asserted that “imperative dedications” constitute an important testimony for Graeco-Roman attitudes regarding the Egyptian gods. They are indicative of a complex relationship between these gods and their adherents, since the distance presupposed by the issuing of a command did not preclude the creation of close ties between the Isiac divinities and their worshippers.
5 Practices for Orchestrating Productive Mathematics Discussions

In addition to being introduced to these 5 practices, readers will have the opportunity to learn how to set the groundwork through setting goals and selecting tasks. These starting points are discussed in depth to emphasize the importance of pre-planning before implementing any type of mathematical task. Throughout the book there are observational case studies that share the lesson implementation strategies that occur in the various classrooms. Teachers and coaches can read and consider the different techniques used in order to compare and contrast the successes and struggles of other educational professionals while underscoring the importance of implementing the 5 practices. In addition, there are “Try This! ” sections at the end of the later chapters to promote practicing the use of the strategies discussed. Finally, in addition to the 5 practices, this resource incorporates two other best practices to deepen meaningful discourse. The first, called “Moves,” deepens the last three practices, while the second, called the Thinking Through a Lesson Protocol (TTLP), scaffolds the planning process through a list of questions.
Review of Input Variable Selection Methods for Artificial Neural Networks

The choice of input variables is a fundamental, and yet crucial consideration in identifying the optimal functional form of statistical models. The task of selecting input variables is common to the development of all statistical models, and is largely dependent on the discovery of relationships within the available data to identify suitable predictors of the model output. In the case of parametric, or semi-parametric empirical models, the difficulty of the input variable selection task is somewhat alleviated by the a priori assumption of the functional form of the model, which is based on some physical interpretation of the underlying system or process being modelled. However, in the case of artificial neural networks (ANNs), and other similarly data-driven statistical modelling approaches, there is no such assumption made regarding the structure of the model. Instead, the input variables are selected from the available data, and the model is developed subsequently. The difficulty of selecting input variables arises due to (i) the number of available variables, which may be very large; (ii) correlations between potential input variables, which creates redundancy; and (iii) variables that have little or no predictive power. Variable subset selection has been a longstanding issue in fields of applied statistics dealing with inference and linear regression (Miller, 1984), and the advent of ANN models has only served to create new challenges in this field. The non-linearity, inherent complexity and non-parametric nature of ANN regression make it difficult to apply many existing analytical variable selection methods. The difficulty of selecting input variables is further exacerbated during ANN development, since the task of selecting inputs is often delegated to the ANN during the learning phase of development. A popular notion is that an ANN is adequately capable of identifying redundant and noise variables during training, and that the trained network will use only the salient input variables. ANN architectures can be built with arbitrary flexibility and can be successfully trained using any combination of input variables (assuming they are good predictors). Consequently, allowances are often made for a large number of input variables, with the belief that the ability to incorporate such flexibility and redundancy creates a more robust model. Such pragmatism is perhaps symptomatic of the popularisation of ANN models through machine learning, rather than statistical learning theory. ANN models are too often developed without due consideration given to the effect that the choice of input variables has on model complexity, learning difficulty, and performance of the subsequently trained ANN. 1
A Sparse Representation Technique For Classification Problems

In pattern recognition and machine learning, a classification problem refers to finding an algorithm for assigning a given input data into one of several categories. Many natural signals are sparse or compressible in the sense that they have short representations when expressed in a suitable basis. Motivated by the recent successful development of algorithms for sparse signal recovery, we apply the selective nature of sparse representation to perform classification. In order to find such sparse linear representation, we implement an l-minimization algorithm. This methodology overcomes the lack of robustness with respect to outliers. In contrast to other classification algorithms such as Support Vector Machines (SVM), no model selection dependence is involved. The minimization algorithm is a convex relaxation-like algorithm that has been proven to efficiently recover sparse signals. To study its performance, the proposed method is applied to six tumor gene expression datasets with a large number of features but few samples. Our numerical results compare favorably with various SVM methods. We also test the effectiveness of our classification algorithm in the Fisher’s Iris dataset where a large number of samples but a small number of features are available. Since the process and techniques for acquiring and analyzing data advance every day at high rates, we need to manage and analyze large amounts of data for several different scientific problems. Future work aims to study the performance of our classification method when dimensionality reduction techniques are applied, including feature selection and feature extraction strategies.
Building Intelligent Interactive Tutors: Student-centered Strategies for Revolutionizing E-learning

Computers have transformed every facet of our culture, most dramatically communication, transportation, finance, science, and the economy. Yet their impact has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. Another reason is that current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. The more instructional software can reason about its own teaching process, know what it is teaching, and which method to use for teaching, the greater is its impact on education. Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. *Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available *Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet *Features algorithmic material that enables programmers and researchers to design building components and intelligent systems
Decisions in resource management

Abstract This study examines management of microforms at libraries and institutions maintaining an active interest in their own microform collections, defined for the purpose of this study as those not only holding, but still acquiring microforms. Survey results presented here, which identify factors that contribute to retention and discard decisions – including holdings of the same content in different formats – are considered in the context of decision theory. Findings could inform current and future decisions relating to the microforms discussed here as well as to holdings in formats dependent on other technologies that will eventually change.
Window flow control in frame-relay networks

Flow-control issues in frame-relay networks are investigated. The intermediate nodes perform the routing and store-and-forward functions. In the case of transmission error or buffer overflow, these nodes simply discard frames. Error recovery and flow control are performed by the end nodes. Simulation results show that a properly tuned dynamic window flow control mechanism provides both good throughput/delay performance and fairness. In the cases considered, a linear window increase strategy performs slightly better than a parabolic one. However, the parabolic strategy is less susceptible to transmission errors. <<ETX>>