Teaching Reading to ESL Adult Literacy Learners: The Development of an Instructor’s Handbook

The purpose of this project was to develop an instructors’ handbook that provides the declarative, procedural, and conditional knowledge associated with the interactive instructional approach, differentiated instruction, and the gradual release of responsibility framework for teaching reading to English as a second language adult literacy learners. The need for this handbook was determined by conducting a critical analysis of existing handbooks and concluding that no handbook completely addressed the 3 types of knowledge for the 3 instructional processes. A literature review was conducted to examine the nature, use, and effectiveness of the 3 instructional processes when teaching reading to ESL adult literacy learners. The literature review also examined teachers’ preferences for reading research and found that texts that were relevant, practical, and accessible were favoured. Hence, these 3 elements were incorporated as part of the handbook design. Three peer reviewers completed a 35-item 5-point Likert scale evaluation form that also included 5 open-ended questions. Their feedback about the handbook’s relevancy, practicality, accessibility, and face validity were incorporated into the final version of the handbook presented here. Reference to the handbook by ESL adult literacy instructors has the potential to support evidence-informed lesson planning which can support the ESL adult literacy learners in achieving their goals and contributing to their societies in multiple and meaningful ways.

Favoriser le transfert de connaissances grammaticales en situation d'écriture : mise à l'essai d'une séquence didactique auprès d'élèves de troisième secondaire

Cette recherche-action vise à déterminer par quels moyens les enseignants de français peuvent contribuer à favoriser le transfert de connaissances grammaticales en situation d’écriture chez leurs élèves de niveau secondaire. Nous avons d’abord constaté que, chez les élèves du secondaire en général, les accords sont plus facilement réussis en contexte d’exercice qu’en contexte de production écrite. Sur la base de propositions didactiques pertinentes concernant l’orthographe grammaticale et/ou le transfert de connaissances, propositions fondées notamment sur une approche inductive, centrée sur le questionnement de l’élève et sur l’analyse de phrases, nous avons conçu et élaboré une séquence didactique portant sur l’accord du participe passé employé avec être ou avec un verbe attributif. Dans un deuxième temps, nous l’avons mise à l’essai auprès d’un groupe d’élèves de troisième secondaire, puis nous en avons vérifié les effets à l’aide d’un prétest et d’un posttest composés respectivement d’un questionnaire, d’un exercice et d’une production écrite. Les résultats révélés par l’analyse des données démontrent l’efficacité de la série de cours. En effet, le taux moyen de réussite des accords en contexte d’exercice passe de 53% à 75%, alors que, pour les productions écrites, il est de 48% avant la série de cours contre 82% après. Les questionnaires recueillis nous portent à attribuer en partie cette forte augmentation du taux de réussite des accords en contexte de production écrite au bon déroulement du processus de transfert grâce au travail effectué en cours de séquence sur les connaissances conditionnelles.

Le transfert des connaissances historiques dans la résolution d'un problème actuel chez les étudiants de niveau collégial

Depuis quelques années déjà, la responsabilité de l’éducation à la citoyenneté est principalement confiée à l’enseignement de l’histoire dans le réseau scolaire québécois. Toutefois, aucune étude expérimentale n’a démontré que l’histoire était la matière la plus apte à éduquer à la citoyenneté. Cette recherche vise donc à savoir si les étudiants de niveau collégial transfèrent leurs connaissances historiques dans la résolution d’un problème d'actualité présentant une connotation historique. Le groupe cible de cette recherche est formé de vingt-cinq étudiants de Sciences humaines (ayant des cours d’histoire) et le groupe contrôle est constitué de vingt-cinq étudiants de Science de la nature (n’ayant pas de cours d’histoire). Durant des entrevues semi-dirigées d’une trentaine de minutes, les étudiants avaient à se prononcer sur une entente signée entre les Innus et les gouvernements fédéral et provincial. Une mise en situation leur était présentée préalablement. Il est ressorti peu de différences entre le groupe cible et le groupe contrôle. Ces deux effectifs considérés ensemble, le quart des répondants n’utilisait aucune connaissance historique. Surtout, la variable influençant le plus le transfert des connaissances historiques s’avère être le sexe. Parmi les répondants n’utilisant aucune connaissance historique, il n’y avait qu’un répondant de sexe masculin; et les seuls répondants à avoir utilisé les connaissances conditionnelles étaient tous de sexe masculin. C’est donc dire que le système scolaire québécois ne favoriserait pas suffisamment le transfert des connaissances historiques dans l’analyse de situations actuelles.

Activités pédagogiques en laboratoire favorisant l'intégration de connaissances conditionnelles

Rapport de stage présenté à la Faculté des sciences infirmières en vue de l’obtention du grade de Maître ès en sciences (M.Sc.) en sciences infirmières option formation en sciences infirmières

Conditional reasoning: A key to assessing computer-based knowledge-building communication processes

This article describes a methodological approach to conditional reasoning in online asynchronous learning environments such as Virtual-U VGroups, developed by SFU, BC, Canada, consistent with the notion of meaning implication: If part of a meaning C is embedded in B and a part of a meaning B is embedded in A, then A implies C in terms of meaning [Piaget 91]. A new transcript analysis technique was developed to assess the flows of conditional meaning implications and to identify the occurrence of hypotheses and connections among them in two human science graduate mixed-mode online courses offered in the summer/spring session of 1997 by SFU. Flows of conditional meaning implications were confronted with Virtual-U VGroups threads and results of the two courses were compared. Findings suggest that Virtual-U VGroups is a knowledge-building environment although the tree-like Virtual-U VGroups threads should be transformed into neuronal-like threads. Findings also suggest that formulating hypotheses together triggers a collaboratively problem-solving process that scaffolds knowledge-building in asynchronous learning environments: A pedagogical technique and an built-in tool for formulating hypotheses together are proposed. © Springer Pub. Co.

Spreadsheet Conditional Formatting Illuminates Investigations into Modular Arithmetic

Modular arithmetic has often been regarded as something of a mathematical curiosity, at least by those unfamiliar with its importance to both abstract algebra and number theory, and with its numerous applications. However, with the ubiquity of fast digital computers, and the need for reliable digital security systems such as RSA, this important branch of mathematics is now considered essential knowledge for many professionals. Indeed, computer arithmetic itself is, ipso facto, modular. This chapter describes how the modern graphical spreadsheet may be used to clearly illustrate the basics of modular arithmetic, and to solve certain classes of problems. Students may then gain structural insight and the foundations laid for applications to such areas as hashing, random number generation, and public-key cryptography.

External knowledge and query strategies in active learning: A study in clinical information extraction

This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.

Tests of Conditional Asset Pricing Models in the Brazilian Stock Market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the 1976-1992 period. We also test a conditional APT model by using the difference between the 30-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from a total of 25 securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be crucial for the appropriate pricing of the portfolios.

Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records

Electronic Medical Record (EMR) has established itself as a valuable resource for large scale analysis of health data. A hospital EMR dataset typically consists of medical records of hospitalized patients. A medical record contains diagnostic information (diagnosis codes), procedures performed (procedure codes) and admission details. Traditional topic models, such as latent Dirichlet allocation (LDA) and hierarchical Dirichlet process (HDP), can be employed to discover disease topics from EMR data by treating patients as documents and diagnosis codes as words. This topic modeling helps to understand the constitution of patient diseases and offers a tool for better planning of treatment. In this paper, we propose a novel and flexible hierarchical Bayesian nonparametric model, the word distance dependent Chinese restaurant franchise (wddCRF), which incorporates word-to-word distances to discover semantically-coherent disease topics. We are motivated by the fact that diagnosis codes are connected in the form of ICD-10 tree structure which presents semantic relationships between codes. We exploit a decay function to incorporate distances between words at the bottom level of wddCRF. Efficient inference is derived for the wddCRF by using MCMC technique. Furthermore, since procedure codes are often correlated with diagnosis codes, we develop the correspondence wddCRF (Corr-wddCRF) to explore conditional relationships of procedure codes for a given disease pattern. Efficient collapsed Gibbs sampling is derived for the Corr-wddCRF. We evaluate the proposed models on two real-world medical datasets - PolyVascular disease and Acute Myocardial Infarction disease. We demonstrate that the Corr-wddCRF model discovers more coherent topics than the Corr-HDP. We also use disease topic proportions as new features and show that using features from the Corr-wddCRF outperforms the baselines on 14-days readmission prediction. Beside these, the prediction for procedure codes based on the Corr-wddCRF also shows considerable accuracy.

Conditional parallelization of nonStrict independence. Procedures and assessmen

This paper presents a conditional parallelization process for and-parallelism based on the notion of non-strict independence, a more relaxed notion than the traditional of strict independence. By using this notion, a parallelism annotator can extract more parallelism from programs. On the other hand, the intrinsic complexity of non-strict independence poses new challenges to this task. We report here on the implementation we have accomplished of an annotator for non-strict independence, capable of producing both static and dynamic execution graphs. This implementation, along with the also implemented independence checker and their integration in our system, have resulted what is, to the best of our knowledge, the first parallelizing compiler based on nonstrict independence which produces dynamic execution graphs. The paper also presents a preliminary assessment of the implemented tools, comparing them with the existing ones for strict independence, which shows encouraging results.

Capturing expert knowledge for threatened species assessments: a case study using NatureServe conservation status ranks

Assessments for assigning the conservation status of threatened species that are based purely on subjective judgements become problematic because assessments can be influenced by hidden assumptions, personal biases and perceptions of risks, making the assessment process difficult to repeat. This can result in inconsistent assessments and misclassifications, which can lead to a lack of confidence in species assessments. It is almost impossible to Understand an expert's logic or visualise the underlying reasoning behind the many hidden assumptions used throughout the assessment process. In this paper, we formalise the decision making process of experts, by capturing their logical ordering of information, their assumptions and reasoning, and transferring them into a set of decisions rules. We illustrate this through the process used to evaluate the conservation status of species under the NatureServe system (Master, 1991). NatureServe status assessments have been used for over two decades to set conservation priorities for threatened species throughout North America. We develop a conditional point-scoring method, to reflect the current subjective process. In two test comparisons, 77% of species' assessments using the explicit NatureServe method matched the qualitative assessments done subjectively by NatureServe staff. Of those that differed, no rank varied by more than one rank level under the two methods. In general, the explicit NatureServe method tended to be more precautionary than the subjective assessments. The rank differences that emerged from the comparisons may be due, at least in part, to the flexibility of the qualitative system, which allows different factors to be weighted on a species-by-species basis according to expert judgement. The method outlined in this study is the first documented attempt to explicitly define a transparent process for weighting and combining factors under the NatureServe system. The process of eliciting expert knowledge identifies how information is combined and highlights any inconsistent logic that may not be obvious in Subjective decisions. The method provides a repeatable, transparent, and explicit benchmark for feedback, further development, and improvement. (C) 2004 Elsevier SAS. All rights reserved.

A Bayesian approach to modeling the conditional density of the inverse controller

The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems. For illustration purposes, the proposed methodology is applied to linear Gaussian systems. © 2004 IEEE.