Raymond S. Pastore, Ph.D.

What is multimedia? Verbal and Non Verbal representations better for

learning than just one (Mayer, 2005) Modality effect

Audio and visual representations are recommended for instructional delivery (Low & Sweller, 2005) This reduces the cognitive load placed on the

learner by allowing them to focus on the image and listen to the narration at the same time.

Split attention principle - When learners split their attention between text and visuals, they are increasing cognitive load because they are trying to integrate two sources of information that are required for comprehension.

But we care about…. Rapid Fastest Cheapest (cost effective) Time Savings Training?

Research Problem

Research Problem Recent research has revealed that audio can be

compressed up to a certain point and still support high level learning (Pastore, 2009)

What is Time Compressed Speech? (Orr & Friedman, 1967) The act of changing the tempo while preserving the pitch and retaining quality Invariant timing hypothesis (Honing, 2007).

This hypothesis states that one cannot distinguish between the quality of audio when there is a tempo change (within normal wpm ranges and up to a certain point of compression).

Pastore (2009) revealed that spoken words could be digitally time-compressed up to 25% in a multimedia environment while preserving complex learning.

Thus, a one-hour multimedia session could take 45 minutes if time-compressed 25% and still maintain the same level of learner comprehension.

Research Problem Redundancy Principle

Would time-compressed speech be more effective if text was provided? This goes against redundancy principle

Current research has revealed a possible reversal effect associated with time-compressed instruction on factual knowledge (Ritzhaupt, Gomes, & Barron, 2008). The reversal effect suggests that groups who

received redundant representations outperformed groups who received non-redundant representations.

At this time however, no research has examined time-compressed instruction and redundancy on high-level learning objectives.

The purpose of this study was to examine 1) the effects of time-compressed

instruction on learning complex material in a multimedia environment

2) the redundancy principle on complex material in a multimedia environment and

3) the impacts of cognitive load on both time-compression and redundancy in a multimedia environment.

Methodology Participants - 154 University Students (61

males/93 females)

Instruction 2,000-word script - based on the physiology and

function of the human heart and its parts (Dwyer, 1965) 19 Simple line drawings Audio Narration

Audio Compression Audacity WSOLA

Design - 2x3 Experimental Design Independent Variables -

Redundant and Non-redundant Compressed Instruction - 0%, 25%, 50%

0% Compression 25% Compression 50% Compression n

Redundant 25 27 25 77

Non-Redundant

25 25 27 77

n 50 52 52 154

- Demographics Survey- Pre-Test- Dependent Variables:

Post Tests - Identification - measures students’ understanding of

factual knowledge Comprehension - measures students’ understanding of

problem solving Cognitive Load – direct subjective measure given

immediately after treatment Time-on-Task Review Behaviors - Back and Replay Buttons

Methodology – Sample without text

Methodology –redundant text

Methodology - Treatments

Compression Percentage - Time

Time Words Per Minute

0% 12:10 164

25% 9:08 219

50% 6:05 328

Methodology - Procedure University Computer lab – Mac lab Each student had their own

headphones/computer station. They were given a CD with treatment

and directions. Study took 45-60 minutes to complete Introduction to study, demographics

survey, pre-test, treatment, DVs

Findings Prior knowledge (2x3 ANOVA) - No differences Posttest Measures (2x3 MANOVA)

Redundancy Non-Redundant (11.78) > Redundant (9.17) – factual Non-Redundant (8.34) > Redundant (7.04) – Problem solving *numbers indicate means; out of 20 points.

Compression (Tukey’s HSD for post hoc) 0% (11.82) = 25% (11.02) > 50% (8.63) - factual 0% (8.84) = 25% (8.25) > 50% (6.02) - Problem solving *numbers indicate means; out of 20 points.

Cognitive Load (2x3 ANOVA) Redundant (3.83) = Non-redundant (3.48) 0% (3.09) = 25% (3.36) > 50% (4.68) *numbers indicate means; out of 7 points; 7 highest load.

Time On Task (2x3 ANOVA): 0% < 25% < 50% Review Behaviors Load (2x3 ANOVA): No significant differences

among groups

Conclusions and Recommendations

The results of both the low (factual) and high (problem solving) level learning tasks in this study revealed that multimedia instruction can be compressed up to 25% without sacrificing learning.

Computer based training should use compressed narration (where appropriate) to take advantage of the speed associated with reading as well as the modality effect

This could translate to significant financial savings when a one-hour computer based training session is reduced to only 45 minutes, which would accumulate more time saved by each employee who completes it

Conclusions and Recommendations Implementation would be most significant

during large-scale training efforts where hundreds or thousands of employees are training at one time.

Essentially there is a large return on investment when choosing to use this technology

Compressing audio takes very little time and effort, thus, it should not significantly impact development time and should not increase development costs as compression can be done using free software

Future Research How it applies to others types of media

(i.e., mobile) Prior Knowledge Preferences Redundancy – limited text

Follow up study What speeds do students prefer? Students given samples of multimedia

and just audio and asked the following: Would you prefer this for learning?

Lectures? Books? Entertainment? Etc. and asked to rate on 7 point scale.

Students taught how to do time compression and surveyed.

Questions? Ray Pastore: rayme.pastore@gmail.com Website and blog: raypastore.com Presentation:

http://raypastore.com/wordpress/2011/11/aect-time-compression-presentation/

Paper citation: Pastore, R. (2012). The effects of time-

compressed instruction and redundancy on learning and learners’ perceptions of cognitive load. Computers & Education, 58(1), 641-651.