Advanced FL learners explaining their writing choices: epistemic attitude as an indicator of problem-solving and strategic knowledge in the on-line revision process

2015 ◽  
Vol 46 (2) ◽  
pp. 146-158 ◽  
Author(s):  
Maarit Mutta ◽  
Marjut Johansson
Keyword(s):  
Problem Solving ◽  
Strategic Knowledge ◽  
Revision Process ◽  
Epistemic Attitude ◽  
On Line

Cognitive control

2021 ◽  
pp. 93-116
Author(s):  
John Toner ◽  
Barbara Gail Montero ◽  
Aidan Moran
Keyword(s):  
Executive Function ◽  
Problem Solving ◽  
Cognitive Control ◽  
Empirical Evidence ◽  
Skill Acquisition ◽  
Mental Representations ◽  
Phenomenological Analysis ◽  
Cognitive Responses ◽  
Expert Performance ◽  
On Line

What role might intuition and deliberation play during the performance of well-learned skills? Dreyfus and Dreyfus’ (1986) influential phenomenological analysis of skill-acquisition proposes that expert performance is guided by non-cognitive responses which are fast, effortless, and intuitive in nature. Although Dreyfus and Dreyfus (1986) recognize that, on occasions (e.g. when performance goes awry for some reason), a form of ‘detached deliberative rationality’ may be used by experts to improve their performance, they see no role for calculative problem solving or deliberation (i.e. drawing on rules or mental representations) when performance is going well. The current chapter counters this argument by drawing on empirical evidence and phenomenological description to argue that skilled performers use cognitive control (an executive function) across a range of sporting situations (i.e. in training, pre-performance routines, on-line skill execution) in order to maintain and enhance performance proficiency.

Experimental Analysis of Man-Computer Problem-Solving

1970 ◽  
Vol 12 (2) ◽  
pp. 187-201 ◽  
Author(s):  
H. Sackmanh
Keyword(s):  
Problem Solving ◽  
Experimental Studies ◽  
Experimental Methods ◽  
Time Sharing ◽  
Computer Communication ◽  
On Line ◽  
The Subject ◽  
Computer Problem ◽  
Human Problem ◽  
Cross Fertilization

Experimental methods and findings in human problem-solving using on-line and off-line computer systems are reviewed. For historical and technical reasons the field of applied man-computer communication has not been the subject of extensive scientific study. The advent of time-sharing systems in the last decade produced an initial body of empirical data from user statistics and experimental studies comparing time-sharing with batch-processing. This body of data is reviewed for its implications to the controversy over batch and time-sharing systems and to the understanding of human behavior in the man-computer setting. Although the available experimental data are meager and tentative, it is already apparent that behavioral principles of human problem-solving and learning theory can account for many of the trends observed. In turn, the theories can be enriched by new leads stemming from studies of man-computer dialog. A plea is made for interdisciplinary cross-fertilization between behavioral and computer sciences to bridge the humanistic lag in man-computer communication.

scholarly journals Novice programmer’s misconception of programming reflected on problem-solving plans

2017 ◽  
Vol 1 (4) ◽  
pp. 14-24 ◽  
Author(s):  
Kyungbin Kwon
Keyword(s):  
Problem Solving ◽  
Natural Language ◽  
Mental Models ◽  
Strategic Knowledge ◽  
Introductory Programming ◽  
Instructional Supports ◽  
Different Types ◽  
Conditional Statements ◽  
Novice Students ◽  
The Way

Understanding the misconception of students is critical in that it identifies the reasons of errors students make and allows instructors to design instructions accordingly. This study investigated the mental models of programming concepts held by pre-service teachers who were novice in programming. In an introductory programming course, students were asked to solve problems that could be solved by utilizing conditional statements. They developed solution plans pseudo-code including a simplified natural language, symbols, diagrams, and so on. Sixteen solution plans of three different types of problems were analyzed. As a result, the students’ egocentric and insufficient programming concepts were identified in terms of the misuse of variables, redundancy of codes, and weak strategic knowledge. The results revealed that the students had difficulty designing solution plans that could be executed by computers. They needed instructional supports to master how to express their solution plans in the way computers run. Problem driven instructional designs for novice students were discussed.

INITIAL EXPERIMENTS ON THE EFFECTS OF SYSTEM DELAY ON ON-LINE PROBLEM SOLVING

1969 ◽  
Author(s):  
Maxwell A. Morfield ◽  
Raymond A. Wiesen ◽  
Mitchell Grossberg ◽  
Douwe B. Yntema
Keyword(s):  
Problem Solving ◽  
System Delay ◽  
On Line

Development of a GSP Integrated Formative Assessment System on Geometric Creativity

2010 ◽  
Vol 108-111 ◽  
pp. 979-984
Author(s):  
Yuan Chen ◽  
Pi Hsia Hung
Keyword(s):  
Problem Solving ◽  
Formative Assessment ◽  
Assessment System ◽  
Intervention Effect ◽  
Geometric Problem ◽  
Interactive Exploration ◽  
Geometric Concepts ◽  
Scoring Rubrics ◽  
On Line ◽  
Exploration Environment

A GSP integrated learning and assessment system (LAS-GSP) is developed to provide students an interactive exploration environment and on-line feedbacks on geometric problem solving. Three tasks of maximal segmentation are developed to investigate the applicability and intervention effect of the system. There are four scoring elements for students’ on line assignments: (1) systematic approaches, (2) correct solutions, (3) originality of representation, and (4) function derived. The characteristics of students’ learning progress are discussed by the scoring rubrics applied. The results suggest abstract geometric concepts can be visualized, internalized, and enhanced at an earlier age, if mind-tool can be effectively implemented.

TFL: an algebraic language to specify the dynamic behaviour of knowledge-based systems

1996 ◽  
Vol 11 (3) ◽  
pp. 253-280 ◽  
Author(s):  
Christine Pierret-Golbreich ◽  
Xavier Talon
Keyword(s):  
Problem Solving ◽  
Formal Language ◽  
Dynamic Behaviour ◽  
Formal Specifications ◽  
Knowledge Based Systems ◽  
Strategic Knowledge ◽  
Data Types ◽  
Strategic Reasoning ◽  
Knowledge Based ◽  
Algebraic Data Types

AbstractTFL, the Task Formal Language, has been developed for integrating the static and dynamic aspects of knowledge based systems. This paper focuses on the formal specification of dynamic behaviour. Although fundamental in knowledge based systems, strategic reasoning has been rather neglected until now by the existing formal specifications. Most languages were generally more focused on the domain and problem-solving knowledge specification than on the control. The formalisation presented here differs from previous ones in several aspects. First, a different representation of dynamic knowledge is proposed: TFL is based on Algebraic Data Types, as opposed to dynamic or temporal logic. Second, dynamic strategic reasoning is emphasised, whereas existing languages only offer to specify algorithmic control. Then, TFL does not only provide the specification of the problem-solving knowledge of the object system, but also of its strategic knowledge. Finally, the dynamic knowledge of the meta-system itself is also specified. Moreover, modularisation is another important feature of the presented language.

Planning and Problem solving Using the Five disc Tower of London Task

1997 ◽  
Vol 50 (1) ◽  
pp. 49-78 ◽  
Author(s):  
Geoff Ward ◽  
Alan Allport
Keyword(s):  
Problem Solving ◽  
Efficient Solutions ◽  
Normal Adult ◽  
Consecutive Series ◽  
Preparation Time ◽  
Tower Of London ◽  
Action Sequences ◽  
On Line ◽  
The Times

This paper investigates the planning and problem-solving abilities of normal adult subjects using a complex version of Shallice's (1982, 1988) Tower of London (TOL) task. Subjects were required to plan a fluent solution to a range of 5-disc TOL puzzles and then execute their formulated plans as fast as possible. The number of errors and the times taken to prepare the most efficient solutions increased monotonically with the number of chunks of subgoal moves. A subgoal move is a move that is essential for the solution of the puzzle, but which does not place a disc into its goal position. A subgoal chunk is a consecutive series of subgoal moves that all transfer discs to and from the same pegs. Furthermore, preparation time was found to be sensitive to a manipulation that increased the number of competing alternative choices, at critical steps in move selection. When subjects planned their action sequences “on-line”, analyses of individual moves and individual move latencies suggested that planning TOL solutions was limited by the difficulty in evaluating and selecting one action (or one subgoal chunk) from the set of competing potential actions at each step in the course of problem solving.

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