The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Barry Miller - One of the best experts on this subject based on the ideXlab platform.

  • the problem of age in second language acquisition influences from language structure and task
    Bilingualism: Language and Cognition, 1999
    Co-Authors: Ellen Bialystok, Barry Miller
    Abstract:

    Three groups of participants were given a grammaticality judgement test based on five structures of English Grammar in both an oral and written form. The first group consisted of native speakers of Chinese, the second, native speakers of Spanish, and the third, native English speakers. The two learner groups were divided into those who had begun learning English at a younger (less than 15 years) or older (more than 15 years) age. Performance was measured for both accuracy of judgement and time taken to respond. The results showed that performance patterns were different for the two learner groups, that the linguistic structure tested in the item affected participants' ability to respond correctly, and that task modality produced reliable response differences for the two learner groups. Although there were proficiency differences in the grammaticality judgement task between the younger and older Spanish learners, there were no such differences for the Chinese group. Furthermore, age of learning influenced achieved proficiency through all ages tested rather than defining a point of critical period. The results are interpreted as failing to provide sufficient evidence to accept the hypothesis that there is a critical period for second language acquisition.

Liu Xianghong - One of the best experts on this subject based on the ideXlab platform.

  • argumentation of embedded relative clause and its illumination on English Grammar teaching
    Journal of Nanjing University of Aeronautics and Astronautics, 2009
    Co-Authors: Liu Xianghong
    Abstract:

    The creative process of embedded relative clause on the basis of branching rules in Generative Transformational Grammar and rankshifted rule in Systemic Functional Grammar indicate that the differences between embedded relative clause and subordinate relative clause are the former's recursiveness and rankshifted construction,and further illustrate the function of this argumentation on Grammar teaching: it proves the validity of pedagogical Grammar and requires for Grammar teachers' mastery of linguistic theory and their guiding functions on the students.

  • demonstration of embedded relative clause and its enlightenment to English Grammar teaching
    Journal of Wenzhou University, 2009
    Co-Authors: Liu Xianghong
    Abstract:

    We have analyzed the creative process of embedded relative clause on the basis of branching rules in the Generative Transformational Grammar and rank shifted rule in Systemic Functional Grammar,indicated that the differences between embedded relative clause and subordinate relative clause are the former's recursiveness and rank shifted construction,and further illustrated the function of this argumentation on Grammar teaching:it proves the validity of pedagogical Grammar and requires for Grammar teachers' mastery of linguistic theory and their guiding functions on the students.

Kenneth R Koedinger - One of the best experts on this subject based on the ideXlab platform.

  • variations in learning rate student classification based on systematic residual error patterns across practice opportunities
    Educational Data Mining, 2015
    Co-Authors: Ran Liu, Kenneth R Koedinger
    Abstract:

    A growing body of research suggests that accounting for studentspecific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a parameter that individualizes for overall student ability but not for student learning rate. Here, we show that adding a per-student learning rate parameter to AFM overall does not improve predictive accuracy. In contrast, classifying students into three “learning rate” groups using residual error patterns, and adding a per-group learning rate parameter to AFM, substantially and consistently improves predictive accuracy across 8 datasets spanning the domains of Geometry, Algebra, English Grammar, and Statistics. In a subset of datasets for which there are preand post-test data, we observe a systematic relationship between learning rate group and pre-topost-test gains. This suggests there is both predictive power and external validity in modeling these distinct learning rate groups.

  • knowledge tracing and cue contrast second language English Grammar instruction
    Cognitive Science, 2013
    Co-Authors: Helen Zhao, Kenneth R Koedinger, John Kowalski
    Abstract:

    Knowledge tracing and cue contrast: Second language English Grammar instruction Helen Zhao (helenz@cuhk.edu.hk) Department of English, The Chinese University of Hong Kong Shatin, Hong Kong Kenneth R. Koedinger (koedinger@cmu.edu) Human-Computer Interaction Institute and Department of Psychology, Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA 15213 USA John Kowalski (jkau@andrew.cmu.edu) Department of Psychology, Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA 15213 USA Abstract This paper introduces a cognitive tutor designed for second language Grammar instruction. The tutor adopted Corbett and Anderson’s (1995) Bayesian knowledge tracing model and provided adaptive training on the English article system. We followed the Competition Model (MacWhinney, 1997) and understood the article system as a galaxy of cues determining article usage on the basis of form-function mapping. Cues are in competition during language acquisition; hence cue contrast is predicted to be an effective instructional method. Seventy-eight students were randomly assigned to four article training conditions (to learn 33 cues) and a control condition (to write essays). We found that article-training groups significantly outperformed the control group in an immediate posttest and a delayed posttest. Specifically, our result also suggested that there was a significant interaction between cue contrast and cue type (definite vs. indefinite). Cue contrast promoted more learning on the indefinite cues (more difficult for learners). Knowledge tracing did not demonstrate such an interactional effect with cue types. Instead, it boosted the instructional effect promoted by cue contrast. Keywords: knowledge tracing; cue contrast; cognitive tutor; second language acquisition; English article. Introduction Since the mid-1990s Corbett & Anderson’s (1995) Bayesian knowledge tracing model has been widely used to model student knowledge in learning systems of various domains, including tutors for mathematics, computer programming, and reading skills (Baker et al., 2010). In recent years, there has been an emergence of tutoring systems designed to facilitate second language learning (MacWhinney, 1995; Pavlik & Anderson, 2005). Among them we rarely find learning systems adopting Bayesian knowledge tracing to promote robust language learning (Koedinger, Corbett & Perfetti, 2012). This paper introduces a Bayesian tutorial system of Grammar instruction applied in an English as a Foreign Language (EFL) context. The primary goal of this research has been to develop an adaptive vehicle for testing the efficacy of Bayesian Knowledge Tracing in this domain. Another feature of the tutor, which presents grammatical cues in contrast, is informed by the cognitive linguistic theories of the Competition Model (MacWhinney, 1997). This paper discusses how these two areas of thought are blended to shape the design of the tutor and how they interact to influence learning effects. Specifically, the tutor targets the English article system, a difficult grammatical category for second language learners (Butler, 2002; Celce- Murcia & Larsen-Freeman, 1999). Bayesian Knowledge Tracing Corbett and Anderson’s (1995) Bayesian knowledge tracing assumes that at any given opportunity to use a rule within the software, there exists a probability that a student knows the rule and may either give a correct or incorrect response. A student who does not know a skill generally will give an incorrect response, but there is a certain probability (called p(G), the Guess parameter) that the student will give a correct response. Correspondingly, a student who does know a skill generally will give a correct response, but there is a certain probability (called p(S), the Slip parameter) that the student will give an incorrect response. Each rule has an initial probability (p(L 0 )) of being known by the student, and at each opportunity to practice a skill, the student has a certain probability (p(T)) of learning the skill. Once these four parameters are set, the model can be used to predict student performance. Figure 1 illustrates the relationship between the four parameters in the Bayesian Knowledge Tracing Model. p(T) Not learned Learned p(L 0 ) 1-p(S) p(G) correct correct Figure 1: Bayesian Knowledge Tracing Model (Corbett and Anderson, 1995) The system’s estimate that a student knows a rule at time n (P(L n )) is continually updated every time the student responds (correctly or incorrectly) to a problem step. First,

Ivana Simonova - One of the best experts on this subject based on the ideXlab platform.

  • Blended approach to learning and practising English Grammar with technical and foreign language university students: comparative study
    Journal of Computing in Higher Education, 2019
    Co-Authors: Ivana Simonova
    Abstract:

    Blended design of teaching/learning foreign languages, in this case English Grammar, has become widely spread within the higher education. The main objective of the article is to discover whether blended approach enhances the process of acquiring new knowledge in the field. The research was conducted at two institutions: faculty of informatics and management, University of Hradec Kralove (technical students) and faculty of education, University of Jan Evangelista Purkyne, Usti nad Labem (foreign language students), Czech Republic. Totally, the research sample included 123 bachelor students. Data were collected in three phases: (1) face-to-face pre-testing to monitor entrance knowledge before the process of blended learning starts, (2) post-testing 1 applied after the blended learning approach and (3) final face-to-face post-testing 2 administered at the end of semester. Phase 1 was followed by autonomous learning from the online course; teacher´s feedback was provided to the students after phase 2 so that they could correct their mistakes, and improve the knowledge in phase 3. Eight hypotheses were tested to discover whether there exist statistically significant differences in test scores between the technical and foreign language students. The results differ according to the students´ level of English knowledge. However, they entitle the described blended learning approach to be applied for acquiring English Grammar for B2 and C1 levels of CEFR.

John Walmsley - One of the best experts on this subject based on the ideXlab platform.

  • the English patient English Grammar and teaching in the twentieth century
    Journal of Linguistics, 2005
    Co-Authors: Richard Hudson, John Walmsley
    Abstract:

    In the first half of the twentieth century, English Grammar disappeared from the curriculum of most schools in England, but since the 1960s it has gradually been reconceptualised, under the influence of linguistics, and now once again has a central place in the official curriculum. Our aim is not only to document these changes, but also to explain them. We suggest that the decline of Grammar in schools was linked to a similar gap in English universities, where there was virtually no serious research or teaching on English Grammar. Conversely, the upsurge of academic research since the 1960s has provided a healthy foundation for school-level work and has prevented a simple return to old-fashioned Grammar-teaching now that Grammar is once again fashionable. We argue that linguists should be more aware of the links between their research and the school curriculum.