Information Technology Reference
In-Depth Information
• Lack of time for different tasks (e.g., to learn a new tool or to develop a visualiza-
tion).
• Technical issues of software visualization tools (e.g., lack of effective develop-
ment tools or lack of reliable software).
• Integration into the courses or the classroom (e.g., time to adapt visualizations to
a course or visualizations may hide important details or concepts).
• Other factors (including lack of evidence of educational effectiveness).
Ben-Bassat Levy and Ben-Ari ( 2007 ) attribute two primary causes to teachers'
negative experience with animation systems: “First, a pedagogical software tool
cannot stand on its own; rather, it must be integrated into the curriculum through
other learning materials such as the textbook. […] Second, to the extent that a soft-
ware tool is intended for independent use by students as opposed to demonstrations
during frontal instruction by the teacher, the issue of the centrality of the teacher
must be taken into account. Centrality appears to be an issue both for experienced
and highly confident teachers, and for those with little experience and low self
confidence.” (p. 250). They conclude that their research highlights “the extreme
importance of issues relating to control. It is not enough to develop a beautiful
and pedagogical useful tool; issues such as easy installation, training courses, and
tutorials are of equal importance because they will increase an educator's feeling
of control. Similarly, training courses should not ignore operational or pedagogical
difficulties that can arise from the use of a software tool. They should address the
changing role of the educator when using the tool, emphasizing that they remain in
control and do not relinquish their central position” (Ben-Bassat Levy and Ben-Ari
( 2008 , p. 172).
Shaffer et al. ( 2010 ) present findings regarding the state of the field of algorithm
visualization based on analysis of a collection of over 500 algorithm visualizations.
They state that many algorithm visualizations are of low quality, and coverage is
skewed toward a few easier topics and suggest that this can make it hard for instruc-
tors to locate what they need.
In order to deepen the understanding of how learners can be involved in an educa-
tional environment that includes visualization, Naps et al. ( 2003 ) define an Engage-
ment Taxonomy. This taxonomy is based on six different forms of learner engagement
with visualization technology, as is described very briefly in what follows:
No viewing: No visualization technology is used at all.
Viewing: Viewing by itself is the most passive form of engagement, but at the
same time is the core form of engagement, since all other forms of engagement
with visualization entail some kind of viewing.
Responding: The key activity in this category is answering questions concern-
ing the visualization presented by the system.
Changing: The key activity in this category allows learners to change the input
of the algorithm under study in order to explore the algorithm's behavior in dif-
ferent cases.
Search WWH ::




Custom Search