Integration of Molecular Modelling Algorithms with Tutorial Instruction: Design of an Interactive Three-Dimensional Computer-Assisted Learning Environment for Exploring Molecular Structure

1995 ◽  
Vol 72 (8) ◽  
pp. 699 ◽  
Author(s):  
D. E. Jackson ◽  
K. Woods ◽  
R. T. Hyde ◽  
P. N. Shaw
Keyword(s):  
Molecular Structure ◽  
Learning Environment ◽  
Molecular Modelling ◽  
Three Dimensional ◽  
Computer Assisted ◽  
Computer Assisted Learning ◽  
Instruction Design

scholarly journals Scaffolding and integrated assessment in computer assisted learning (CAL) for children with learning disabilities

2005 ◽  
Vol 21 (2) ◽  
Author(s):  
Ivan L. Beale
Keyword(s):  
Learning Disabilities ◽  
Learning Environment ◽  
Integrated Assessment ◽  
Computer Assisted ◽  
Design Strategies ◽  
Learning Context ◽  
Computer Assisted Learning ◽  
Intelligent Learning Environment ◽  
Basic Reading Skills ◽  
Instructional Procedures

<span>Computer assisted learning (CAL) can involve a computerised intelligent learning environment, defined as an environment capable of automatically, dynamically and continuously adapting to the learning context. One aspect of this adaptive capability involves automatic adjustment of instructional procedures in response to each learner's performance, to facilitate the ease of learning and to minimise errors during learning. This process of dynamically varying the help provided to the learner by the instructor has been termed scaffolding. A bonus from using scaffolding is that the programming algorithms by which scaffolding is achieved allow integrated assessment of the learner's performance. This paper outlines the nature and origins of scaffolding concepts and illustrates their application as instructional design strategies in an experimental intelligent learning environment designed to teach basic reading skills to children with learning disabilities. The paper also illustrates the role of integrated assessment as an essential component of scaffolding and as a means of monitoring and recording the learning process.</span>

scholarly journals The Problem Frames Approach to a Virtual Laboratory Conception

2006 ◽  
Vol 5 (1) ◽  
Author(s):  
Nicolas Pagès ◽  
Monique Noirhomme-Fraiture
Keyword(s):  
Learning Environment ◽  
Learning Environments ◽  
Virtual Laboratory ◽  
Computer Assisted ◽  
Computer Assisted Learning ◽  
Problem Frames

This paper presents a virtual laboratory’s conception. It is based on the problem frames approach and involves tke adaptation to computer assisted learning environments. It enphasizes the necessity of defining a certain number of new problem frames in order to adapt it to a learning environment, and particularly to simulations. We present the application of this conception method to the SAI project.

Computer Assisted Image Reconstruction of Oligomer Structure

1976 ◽  
Vol 34 ◽  
pp. 472-473
Author(s):  
A.M. Jones ◽  
A. Max Fiskin
Keyword(s):  
Three Dimensional ◽  
Depth Of Field ◽  
Computer Assisted ◽  
Projection Data ◽  
Two Dimensional ◽  
Single Particles ◽  
Dimensional Reconstruction ◽  
Computer Assisted Image ◽  
The Fourier Transform ◽  
Space Approach

If the tilt of a specimen can be varied either by the strategy of observing identical particles orientated randomly or by use of a eucentric goniometer stage, three dimensional reconstruction procedures are available (l). If the specimens, such as small protein aggregates, lack periodicity, direct space methods compete favorably in ease of implementation with reconstruction by the Fourier (transform) space approach (2). Regardless of method, reconstruction is possible because useful specimen thicknesses are always much less than the depth of field in an electron microscope. Thus electron images record the amount of stain in columns of the object normal to the recording plates. For single particles, practical considerations dictate that the specimen be tilted precisely about a single axis. In so doing a reconstructed image is achieved serially from two-dimensional sections which in turn are generated by a series of back-to-front lines of projection data.

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