Complexiteit en Instructie

2000 ◽  
Vol 63 ◽  
pp. 105-116
Author(s):  
Nel de Jong
Keyword(s):  
Learning Effect ◽  
Explicit Knowledge ◽  
Complex Structure ◽  
Implicit Knowledge ◽  
Grammatical Structure ◽  
Input Enhancement ◽  
Definition Of ◽  
Syntactic Properties ◽  
Types Of Instruction ◽  
Grammatical Structures

There are many ways to teach grammatical structures. In this research, two types of instruction have been investigated. One was rule instruction: the rules were explained to the learners. The other was input enhancement: the learners were given correct examples in which the relevant elements were made salient by bold print and italics. The structures differed in complexity. There were a simple, a complex and a very complex structure. The complexity was determined using De Graaff s (1997) definition. The aim was to find out whether a grammatical structure can be too complex to be acquired as a result of instruction. Rule instruction turned out to have a learning effect for all structures. It leads to some explicit knowledge, but probably also to implicit knowledge. Input enhancement only had a learning effect for the simple structure. It probably, only leads to implicit knowledge: explicit knowledge could not be observed. De Graaff s definition of complexity turned out to be insufficiently specified. It does not distinguish between formal and functional complexity. Furthermore, within formal complexity, syntactic properties of words and word order features should be distinguished.

scholarly journals Der Däne[NGr Nom] ist[Vfin] gemütlich[ADJGr] Nationale Stereotype aus dem SMiK-Projekt und Kritische Grammatik im Deutschunterricht

2016 ◽  
Vol 79 (5) ◽  
Author(s):  
Jörg Kilian
Keyword(s):  
Explicit Knowledge ◽  
Classroom Discussion ◽  
Grammatical Structure ◽  
School Students ◽  
Grammar Teaching ◽  
Linguistic Research ◽  
Linguistic Categories ◽  
Grammatical Structures ◽  
National Stereotypes

One of the most frequently used grammatical structures to express national stereotypes in German is the sentence pattern X [NGr Nom] ist [Vfin] Y [ADJGr]. Within the framework of linguistic research on stereotypes this structure has been described in great detail so that its syntactic, semantic, and socio-pragmatic dimensions are known rather well. Results of the SMiK-project confirm the important role this pattern plays in expressing stereotypes. As to grammar teaching at school, however, this grammatical structure is rarely discussed in textbooks and, assumingly, in classrooms. This paper presents an approach to make this structure a subject of classroom discussion. The approach is based on a didactic concept of “critical grammar” in German lessons and aims at making school students aware that explicit knowledge about grammatical structures is not only (if at all) knowledge about linguistic categories for the purpose of filing language into scientific regulations or rules but an instrument to discover and to elucidate “pictures in our heads”.

Hoe Beïnvloedt Kennis Over Taal de Verwerving Van Een Vreemde Taal? Evidentie Vanuit Een Computeronder-Steunde Cursus Spaans

1998 ◽  
Vol 58 ◽  
pp. 119-126
Author(s):  
Rick de Graaff
Keyword(s):  
Explicit Knowledge ◽  
Explicit Instruction ◽  
Syntactic Structure ◽  
Morphological Structure ◽  
Implicit Knowledge ◽  
Target Language ◽  
Computer Assisted ◽  
Grammatical Structure ◽  
Self Study ◽  
Knowledge Of Language

The article reports on an empirical study of the faciltative effect of explicit instruction about language structure on the acquisition of second language (L2) morphosyntax, by means of an experiment in which students learning Spanish were given varying amounts of explanation about the grammatical structure. Students took a computer-assisted self-study course under explanation or non-explanation conditions, and were tested on the acquisition of a simple and a complex morphological structure and a simple and a complex syntactic structure. It is argued that explicit knowledge about language does not convert into implicit knowledge of language. The study is based on an attention focusing position, according to which implicit knowledge is acquired as a result of noticing specific forms and their meanings in the target language; noticing can be facilitated by explicit knowledge built up as a result of explicit instruction.

Implicit knowledge as automatic, latent knowledge

1999 ◽  
Vol 22 (5) ◽  
pp. 787-788 ◽  
Author(s):  
John R. Vokey ◽  
Philip A. Higham
Keyword(s):  
Knowledge Representation ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Practical Matter ◽  
Definition Of ◽  
Implicit And Explicit

Implicit knowledge is perhaps better understood as latent knowledge so that it is readily apparent that it contrasts with explicit knowledge in terms of the form of the knowledge representation, rather than by definition in terms of consciousness or awareness. We argue that as a practical matter any definition of the distinction between implicit and explicit knowledge further involves the notion of control.

Patterns of Implicit Learning Below the Level of Conscious Knowledge

2010 ◽  
Vol 24 (2) ◽  
pp. 91-101 ◽  
Author(s):  
Juliana Yordanova ◽  
Rolf Verleger ◽  
Ullrich Wagner ◽  
Vasil Kolev
Keyword(s):  
Implicit Learning ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Knowledge Generation ◽  
Sleep Stages ◽  
Implicit Processing ◽  
Implicit Processes ◽  
Late Night ◽  
On Line ◽  
On Line Learning

The objective of the present study was to evaluate patterns of implicit processing in a task where the acquisition of explicit and implicit knowledge occurs simultaneously. The number reduction task (NRT) was used as having two levels of organization, overt and covert, where the covert level of processing is associated with implicit associative and implicit procedural learning. One aim was to compare these two types of implicit processes in the NRT when sleep was or was not introduced between initial formation of task representations and subsequent NRT processing. To assess the effects of different sleep stages, two sleep groups (early- and late-night groups) were used where initial training of the task was separated from subsequent retest by 3 h full of predominantly slow wave sleep (SWS) or rapid eye movement (REM) sleep. In two no-sleep groups, no interval was introduced between initial and subsequent NRT performance. A second aim was to evaluate the interaction between procedural and associative implicit learning in the NRT. Implicit associative learning was measured by the difference between the speed of responses that could or could not be predicted by the covert abstract regularity of the task. Implicit procedural on-line learning was measured by the practice-based increased speed of performance with time on task. Major results indicated that late-night sleep produced a substantial facilitation of implicit associations without modifying individual ability for explicit knowledge generation or for procedural on-line learning. This was evidenced by the higher rate of subjects who gained implicit knowledge of abstract task structure in the late-night group relative to the early-night and no-sleep groups. Independently of sleep, gain of implicit associative knowledge was accompanied by a relative slowing of responses to unpredictable items suggesting reciprocal interactions between associative and motor procedural processes within the implicit system. These observations provide evidence for the separability and interactions of different patterns of processing within implicit memory.

Diagnosis Rule Discovery Based on Causality in the Context of Fault Diagnosis in Rotating Machinery

2014 ◽  
Vol 532 ◽  
pp. 113-117
Author(s):  
Zhou Jin ◽  
Ru Jing Wang ◽  
Jie Zhang
Keyword(s):  
Fault Diagnosis ◽  
General Framework ◽  
Complex Structure ◽  
Rotating Machinery ◽  
Massive Data ◽  
Formal Definition ◽  
Rule Discovery ◽  
Rule Based ◽  
Simple Implementation ◽  
Definition Of

The rotating machineries in a factory usually have the characteristics of complex structure and highly automated logic, which generated a large amounts of monitoring data. It is an infeasible task for uses to deal with the massive data and locate fault timely. In this paper, we explore the causality between symptom and fault in the context of fault diagnosis in rotating machinery. We introduce data mining into fault diagnosis and provide a formal definition of causal diagnosis rule based on statistic test. A general framework for diagnosis rule discovery based on causality is provided and a simple implementation is explored with the purpose of providing some enlightenment to the application of causality discovery in fault diagnosis of rotating machinery.

scholarly journals Beyond paradigm: The ‘what’ and the ‘how’ of classroom research

2014 ◽  
Vol 30 (4) ◽  
pp. 551-568 ◽  
Author(s):  
Melinda Whong ◽  
Kook-Hee Gil ◽  
Heather Marsden
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Development ◽  
Explicit Knowledge ◽  
Teaching Practice ◽  
Implicit Knowledge ◽  
Developmental Differences ◽  
Classroom Research ◽  
Language Classroom ◽  
Implicit And Explicit

This article reviews studies in second language classroom research from a cross-theoretic perspective, arguing that the classroom holds the potential for bringing together researchers from opposing theoretical orientations. It shows how generative and general cognitive approaches share a view of language that implicates both implicit and explicit knowledge, and that holds a bias towards implicit knowledge. Arguing that it is implicit knowledge that should be the object of research, it proposes that classroom research would benefit from incorporating insights from a generative understanding of language. Specifically, there is a need for a more nuanced view of the complexity of language in terms of linguistic domain, and the interaction between those domains. Generative second language acquisition research that shows developmental differences in terms of both linguistic domain and interface is reviewed. The core argument is a call for more attention to the ‘what’ of language development in classroom research and, by implication, teaching practice. As such, the language classroom is seen to offer potential for research that goes beyond paradigm to address both the ‘what’ and the ‘how’ of language development.

scholarly journals Convergent and Distinct Effects of Multisensory Combination on Statistical Learning Using a Computer Glove

2021 ◽  
Vol 11 ◽  
Author(s):  
Christopher R. Madan ◽  
Anthony Singhal
Keyword(s):  
Statistical Learning ◽  
Visual Cues ◽  
Explicit Knowledge ◽  
Reaction Time Task ◽  
Musical Instrument ◽  
Implicit Knowledge ◽  
Auditory Cues ◽  
Motor Movements ◽  
Explicit And Implicit Knowledge ◽  
Single Modality

Learning to play a musical instrument involves mapping visual + auditory cues to motor movements and anticipating transitions. Inspired by the serial reaction time task and artificial grammar learning, we investigated explicit and implicit knowledge of statistical learning in a sensorimotor task. Using a between-subjects design with four groups, one group of participants were provided with visual cues and followed along by tapping the corresponding fingertip to their thumb, while using a computer glove. Another group additionally received accompanying auditory tones; the final two groups received sensory (visual or visual + auditory) cues but did not provide a motor response—all together following a 2 × 2 design. Implicit knowledge was measured by response time, whereas explicit knowledge was assessed using probe tests. Findings indicate that explicit knowledge was best with only the single modality, but implicit knowledge was best when all three modalities were involved.

scholarly journals Problems in Grammatical Structure: A Case Study of B.Ed. Student at the Education Department

sjesr ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 420-425
Author(s):  
Dr. Gulzar Ahmed ◽  
Dr. Syed Shafqat Ali Shah ◽  
Dr. Muhammad Nisar
Keyword(s):  
Undergraduate Students ◽  
Quantitative Research ◽  
English Language ◽  
Text Structure ◽  
Grammatical Structure ◽  
Education Department ◽  
Undergraduate Level ◽  
English Grammar ◽  
Grammatical Structures

English grammar is how words in the English language are translated into text. This includes the structure of words, phrases, clauses, and phrases, up to and including full-text structure. The main objective of the authors is to discover the difficulties of grammatical structures for students at the Department of Teacher Education. Shikarpur Shaikh Ayaz University. The students of B.Ed. undergraduate level of education department was selected as a data population. The fifty students were randomly selected from the education department. There is quantitative research underway. The researchers used a testing tool for a questionnaire. The student's collected data were analyzed by SPSS-Descriptive statistics.  Some of the challenges and problems are facing during the English Grammar lesson of B.Ed. students. The students have used the conditional verb and also the proper use of a phrasal verb that is one of the problems with students. The use of an article is also one of the fundamental problems for undergraduate students. Teachers should make it possible for students to practice these materials either through activity-based teaching or through the CLT method so that they can be more attentive to EFL learning and not focus on translation alone.

scholarly journals Assumptions of the Process-Dissociation Procedure are Violated in Implicit Sequence Learning

2016 ◽  
Author(s):  
Marius Barth ◽  
Christoph Stahl ◽  
Hilde Haider
Keyword(s):  
Sequence Learning ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Process Dissociation ◽  
Implicit Sequence Learning ◽  
Generation Task ◽  
Accurate Performance ◽  
Exclusion Condition ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

In implicit sequence learning, a process-dissociation (PD) approach has been proposed to dissociate implicit and explicit learning processes. Applied to the popular generation task, participants perform two different task versions: inclusion instructions require generating the transitions that form the learned sequence; exclusion instructions require generating transitions other than those of the learned sequence. Whereas accurate performance under inclusion may be based on either implicit or explicit knowledge, avoiding to generate learned transitions requires controllable explicit sequence knowledge. The PD approach yields separate estimates of explicit and implicit knowledge that are derived from the same task; it therefore avoids many problems of previous measurement approaches. However, the PD approach rests on the critical assumption that the implicit and explicit processes are invariant across inclusion and exclusion conditions. We tested whether the invariance assumptions hold for the PD generation task. Across three studies using first-order as well as second-order regularities, invariance of the controlled process was found to be violated. In particular, despite extensive amounts of practice, explicit knowledge was not exhaustively expressed in the exclusion condition. We discuss the implications of these findings for the use of process-dissociation in assessing implicit knowledge.

Human Factors in Interactive Machine Learning: A Cybersecurity Case Study

2021 ◽  
Vol 65 (1) ◽  
pp. 1495-1499
Author(s):  
Mark H. Chignell ◽  
Mu-Huan Chung ◽  
Yuhong Yang ◽  
Greg Cento ◽  
Abhay Raman
Keyword(s):  
Machine Learning ◽  
Human Factors ◽  
Financial Services ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Cyber Attacks ◽  
Transfer Data ◽  
Interactive Machine Learning

Cybersecurity is emerging as a major issue for many organizations and countries. Machine learning has been used to recognize threats, but it is difficult to predict future threats based on past events, since malicious attackers are constantly finding ways to circumvent defences and the algorithms that they rely on. Interactive Machine learning (iML) has been developed as a way to combine human and algorithmic expertise in a variety of domains and we are currently applying it to cybersecurity. In this application of iML, implicit knowledge about human behaviour, and about the changing nature of threats, can supplement the explicit knowledge encoded in algorithms to create more effective defences against cyber-attacks. In this paper we present the example problem of data exfiltration where insiders, or outsiders masquerading as insiders, who copy and transfer data maliciously, against the interests of an organization. We will review human factors issues associated with the development of iML solutions for data exfiltration. We also present a case study involving development of an iML solution for a large financial services company. In this case study we review work carried out on developing visualization dashboards and discussing prospects for further iML integration. Our goal in writing this paper is to motivate future researchers to consider the role of the human more fully in ML, not only in the data exfiltration and cybersecurity domain but also in a range of other applications where human expertise is important and needs to combine with ML prediction to solve challenging problems.

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