a rationale for multi-modality in multimedia instructional design sanja kisicek, tomislava lauc...

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A Rationale for Multi- modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of Zagreb {smatic, tlauc}@ffzg.hr

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Page 1: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

A Rationale for Multi-modality in

Multimedia Instructional Design

Sanja Kisicek, Tomislava Lauc

Faculty of Humanities and Social SciencesUniversity of Zagreb{smatic, tlauc}@ffzg.hr

Page 2: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

?

Page 3: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of
Page 4: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

What is this all about?• a multi-modal approach to multimedia

instructional deign in a virtual learning environment

• how multimedia and multimodal?– one e-course (Moodle)– 10 lessons– 3 different types of resources

Page 5: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

What is the purpose of the research?

To investigate user perceptual modalities in terms of their preferences towards using a

certain type of educational media in computer literacy acquisition

Page 6: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

The Rationale

User preferences in a multimedia learning environment can be supported if users

are provided with a possibility to choose the way in which they will perceive

information.

Page 7: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

To further substantiate…• one-size-fits-all approach does not fit• there are different individualization strategies:– recommender systems– adaptive hypermedia– adapting various explanations• control given to the user

Page 8: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

The real question is

How to facilitate acquiring computer literacy by making it appealing to one

user and at the same time to any other?

Page 9: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

Possible answer:

By accommodating different perceptual modalities in a virtual

learning environment and conducting research on user behavior.

Page 10: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

The Research• Department of Information and

Communication Sciences • Faculty of Humanities and Social Sciences • The University of Zagreb• Course: Socio-Humanistic Informatics – elective, enrolls more than 100 students yearly– weekly lessons strictly build on each other– 98 students; 82 females and 16 males

Page 11: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

Sample (N=98)

Page 12: A Rationale for Multi-modality in Multimedia Instructional Design Sanja Kisicek, Tomislava Lauc Faculty of Humanities and Social Sciences University of

Methodology• Modelling user activity• The strategy for modelling user activity in accessing resources

• Specifying data– defining the number of users (98 students),– choosing objects for tracking access (30 resources) – defining the type of access (resource view)

• Constructing the series– defining the type and the number of samples (30 resources) – defining the values from the series’ data (the frequency of access)

• Obtaining the similarity matrix – defining the similarity measure (cosine) – defining the linkage method (complete linkage)

• Identifying the obtained clusters which are visualized by a dendrogram