Do Metacognitive Strategies Improve Student Achievement in Secondary Science Classrooms?

Increasing prevalence of high-stakes testing calls for focus on value-added teaching and learning practices. Following is an inquiry regarding metacognitive teaching and learning practices as it pertains to secondary science classrooms. Research shows that the orchestration and inclusion of metacognitive strategies in the science classroom improve achievement under the following preconditions: (1) are pervasively embedded in the educational structure; (2) are part of appropriately rigorous and relevant curriculum; (3) are supported by ‘metacognitive friendly’ teaching strategies; (4) are explicitly practiced by students and teachers; and (5) enable students to take responsibility for their own learning

Grammar Learning Strategies and Language Attainment: Seeking a Relationship

Despite major advances in research on language learning strategies, there are still areas that have received only scant attention, and one of them is undoubtedly learning grammar. The paper contributes to the paucity of empirical investigations in this domain by presenting the findings of a study which sought to investigate the relationship between the use of grammar learning strategies (GLS) reported by 142 English Department students and target language attainment, operationalized as their performance in a practical grammar course and the end-of-the-year examination. Information about GLS use was obtained by means of a tool that was designed on the basis of a theoretical scheme proposed by Oxford, Rang Lee and Park (2007) in which GLS are divided into three categories depending on whether they represent implicit learning with focus on form, explicit inductive learning and explicit deductive learning. The analysis failed to find a strong positive relationship between the use of GLS and achievement, irrespective of the level of the BA program, or statistically significant differences in this respect between lower-level and higher-level participants. The highest, albeit very weak, correlation was identified between the use of GLS associated with explicit deductive learning and grammar course grades, which testifies to the traditional nature of instruction the subjects receive. The findings serve as a basis for putting forward a handful of recommendations for learning, teaching and testing grammar as well as directions for future studies into grammar learning strategies

Econometrics for Learning Agents

The main goal of this paper is to develop a theory of inference of player valuations from observed data in the generalized second price auction without relying on the Nash equilibrium assumption. Existing work in Economics on inferring agent values from data relies on the assumption that all participant strategies are best responses of the observed play of other players, i.e. they constitute a Nash equilibrium. In this paper, we show how to perform inference relying on a weaker assumption instead: assuming that players are using some form of no-regret learning. Learning outcomes emerged in recent years as an attractive alternative to Nash equilibrium in analyzing game outcomes, modeling players who haven't reached a stable equilibrium, but rather use algorithmic learning, aiming to learn the best way to play from previous observations. In this paper we show how to infer values of players who use algorithmic learning strategies. Such inference is an important first step before we move to testing any learning theoretic behavioral model on auction data. We apply our techniques to a dataset from Microsoft's sponsored search ad auction system

THE EFFECT OF LEARNING STRATEGIES SIMULATION AND LEARNING MOTIVATION ON THE RESULTS OF ISLAMIC EDUCATION LEARNING SCHOOL STUDENTS MIDDLE FIRST STATE 4 MEDAN

The research study aims to identify and describe: (1) the effect of implementing learning strategies on the learning outcomes of Islamic Religious Education students at SMP Negeri 4 Medan, (2) the influence of learning motivation on the learning outcomes of Islamic Religious Education students at SMP Negeri 4 Medan, and (3) interaction. between learning strategies and learning motivation on learning outcomes of Islamic Religious Education students of SMP Negeri 4 Medan. The population was all students of class VII SMPN 4 Medan consisting of 11 classes. The sampling technique used was cluster random sampling. The data collection instruments were questionnaires and tests. Testing for normality using Liliefors and homogeneity testing using Fisher and Bartlett. The data analysis technique is a two-way analysis of variance at α = 0.05 .The results showed: (1) there is an effect of the application of learning strategies on learning outcomes of learning outcomes in Islamic Religious Education, this is evident from the results of statistical tests which show Fcount = 4.35 > Ftable 3.96, (2) there is an effect of learning motivation on the results. learning Islamic Religious Education, this is evident from statistical testing which shows Fcount = 5.14 > Ftable 3.96, and (3) there is an interaction between learning strategies and learning motivation, this is evident from statistical testing which shows Fcount = 104.36 > Ftable 3,96

Predicting academic achievement: The role of Motivation and Learning Strategies

The aim of this study consists in testing a predictive model of academic achievement including motivation and learning strategies as predictors. Motivation is defined as the energy and the direction of behaviors; it is categorized in three types of motivation –intrinsic, extrinsic and amotivation (Deci & Ryan, 1985). Learning strategies are deliberate operations oriented towards information processing in academic activities (Valle, Barca, González & Núñez, 1999). Several studies analysed the relationship between motivation and learning strategies in high school and college environments. Students with higher academic achievement were intrinsically motivated and used a wider variety of learning strategies more frequently. A non-experimental predictive design was developed. The sample was composed by 459 students (55.2% high-schoolers; 44.8% college students). Data were gathered by means of sociodemographic and academic surveys, and also by the local versions of the Academic Motivation Scale –EMA, Echelle de Motivation en Éducation (Stover, de la Iglesia, Rial Boubeta & Fernández Liporace, 2012; Vallerand, Blais, Briere & Pelletier, 1989) and the Learning and Study Strategies Inventory –LASSI (Stover, Uriel & Fernández Liporace, 2012; Weinstein, Schulte & Palmer, 1987). Several path analyses were carried out to test a hypothetical model to predict academic achievement (Kline, 1998). Results indicated that self-determined motivation explained academic achievement through the use of learning strategies. The final model obtained an excellent fit (χ2=16.523, df= 6, p=0.011; GFI=0.987; AGFI=0.955; SRMR=0.0320; NFI=0.913; IFI=0.943; CFI=0.940). Results are discussed considering Self Determination Theory and previous research.Fil: Stover, Juliana Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; ArgentinaFil: Freiberg Hoffmann, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; ArgentinaFil: de la Iglesia, Guadalupe. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernandez Liporace, Maria Mercedes. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Exploratory datamorphic testing of classification applications

Testing has been widely recognised as difficult for AI applications. This paper proposes a set of testing strategies for testing machine learning applications in the framework of the datamorphism testing methodology. In these strategies, testing aims at exploring the data space of a classification or clustering application to discover the boundaries between classes that the machine learning application defines. This enables the tester to understand precisely the behaviour and function of the software under test. In the paper, three variants of exploratory strategies are presented with the algorithms as implemented in the automated datamorphic testing tool Morphy. The correctness of these algorithms are formally proved. The paper also reports the results of some controlled experiments with Morphy that study the factors that affect the test effectiveness of the strategies

How people with diabetes integrate self-monitoring of blood glucose into their self-management strategies

Background The benefit of self-monitoring of blood glucose by patients has been questioned, and UK policy is generally not to support this, although it is identified that there may be unidentified subgroups of people who would benefit from being supported to self-monitor. The purpose of this paper is to explore the self-management approaches of people with diabetes, and how self-testing of blood glucose contributes to self-management strategies. Methods This qualitative study of patients’ experiences drew data from contributors to online discussion boards for people living with diabetes. The principles of qualitative content analysis were used on posts from a sample of four Internet discussion boards. Results Contributors described how they were using self-testing within their self-management strategies. Most saw it as a way of actively maintaining control of their condition. The amount of testing carried varied over time; more testing was done in the early days, when people were still learning how to stay in control of their diabetes. Some people had experienced a lack of support for self-testing from healthcare professionals, or had been expected to change their self-management to fit national policy changes. This was seen as unhelpful, demotivating, stressful, and harmful to the doctor–patient relationship. Conclusions The Internet is a valuable source of information about peoples’ self-management behaviours. Patients who are using, or who wish to use, self-testing as part of their self-management strategy are one of the subgroups for whom self testing is beneficial and who should be supported to do so

The Study of Mastery Testing Strategy Versus an Averaging Testing Strategy

In addition to the traditional learning style, an alternative approach is mastery learning. Traditional classroom settings typically include lectures and seat work. These methods are believed to support a masculine style of learning, as they are more individualistic and competitive. Boys tend to respond to questions quickly and confidently. Girls tend to wait longer and choose words more carefully. This leads to male students dominating the classroom. Mastery learning encourages a more cooperative style of learning. Mastery learning theorizes that if students are given the necessary amount of time needed to attain a mastery of a skill, and if the student spent that much time learning the skill, then the student would reach mastery. This master thesis examined the two different testing strategies to see if mastery learning can be appropriate for use in the school system. The study compared two testing strategies in a high school Regents chemistry class. The first allowed students to retake tests and quizzes up to three times, if desired, and the average for all taken would be recorded. The second strategy demanded an 80% or higher mastery level for each unit. Failure to reach 80% would result in a zero. Possible grades for this strategy were 0, 80, 90, and 100. Two teachers used both testing strategies using traditional methods alongside cooperative activities. Results show that there is no significant difference between testing strategies when examining exam averages and passing percentages, however students had a significantly higher percentage of achieving an 80 or higher in the mastery testing strategy. Girls in particular performed much better with the mastery strategy than with the averaging strategy