THE EFFECT OF THE WEB-BASED MULTIPLE INTELLIGENCES AND HIGH ORDER THINKING

SKILLS INSTRUCTION

Hanafi Atan, Noor A.M. Noor, Omar Majid School of Distance Education

Universiti Sains Malaysia,11800 Penang, Malaysia

Yoon Tiem Leong School of Physics

Universiti Sains Malaysia, 11800 Penang, Malaysia

Wong Su Luan Faculty of Education

Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia

Fong Soon Fook School of Educational Studie,

Universiti Sains Malaysia,11800, Penang, Malaysia

ABSTRACT

This paper reports on the investigation of the effect on learning enhancement when the Multiple Intelligence Web-based Learning (MIWBL) and high order thinking skills approach was used in the delivery of a first year undergraduate Physics course. The MIWBL approach involved the design of the course content using the dominant characteristics of the students’ multiple intelligences in combination with the Bloom taxonomy high order thinking skills to form a multiple intelligence learning activity matrix. This matrix allows the incorporation of various learning activities that conform not only to the dominant students’ multiple intelligence characteristics but also high order thinking skills instructional strategies. Learning enhancement was measured by comparing the post-test score achieved by the students when exposed to the MIWBL approach compared of those exposed to the commonly used Web Content-based Learning (CWBL) approach. The comparative post-test performance analysis conducted using a student t-test statistical analysis (p<0.05) revealed that the experimental MIWBL approach yielded better performances than the controlled CWBL approach. Even though there are possible experimental limitations when the exposure was carried out, but nonetheless the results indicate the strength of the MIWBL approach with students responded more positively and yielded better learning outcomes than the control CWBL.

KEYWORDS

Web-based Learning, Multiple Intelligence, High Order Thinking, Adaptive Learning System, Instructional Design, Learning Management System

1. INTRODUCTION

The advancement of information and communication technology (ICT) has led to an enormous shift in the way education is being delivered. One of the important developments of this advancement is the availability of various forms of the open source Learning Management System (LMS). The LMS allows the integration of students and course catalogue databases as well as the incorporation of various features, such as instructor

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tools, instructional features, student tools, technical support, administrative tools and administrative features, all of which are suitable for the incorporation of various learning approaches in education. However, most of the instructional strategies of the course content delivery in the LMS are mainly based on the Web Content-based Learning (WCBL) approach that elicits cognitive processes only for information retrieval (Hanafi et al., 2004). Such strategies lack student engagement that helps to promote and stimulate higher order thinking skills (Dori et al., 2003; Morgan, 1996).

The higher order thinking skills often relate to the Bloom taxonomy category of thinking skills. This taxonomy categorises thinking skills from concrete to abstract and include skills such as knowledge, comprehension, application, analysis, synthesis and evaluation (Bloom, 1956). The last three categories, namely, analysis, synthesis and evaluation, are widely considered as higher order thinking skills as they represent a multi-faceted and complex thinking process associated with learning activities pertaining to concept formation and problem solving (Cradler, 2002; Yuretich, 2004). The instructional design in course delivery using the LMS can be accordingly designed to foster these higher order thinking skills through learning activities that develop the students’ meaningful cognitive operation in the acquisition of new knowledge, enhancing their ability to grasp the interrelationship between new and old ideas.

Apart from instructional activities leading to higher order thinking skills, educators are well aware of the other potential of the LMS. Its strength in teaching and learning is that it allows the integration of the dynamic Website with communication, collaboration and presentation tools to offer course content to learners and allow them to interact with their peers and tutors online regardless of spatial and temporal limitations. However, there is a wide belief that using the Web as only a new kind of delivery medium for educational materials does not add significant value to the teaching and learning process (Santally & Senteni, 2005). The integration of technology in learning needs to address the very important issue of enhancing the teaching and learning process, rather than just viewing it as a new flexible delivery medium (Nichols, 2003). It is postulated that one of the main problems with e-learning environments is their lack of personalisation (Rumetshofer & Wöß, 2003). This is because students prefer to learn in ways that are different from other people of the same class, culture or religion because each one of them is different with their characteristics and methods of processing information. This individual preference of how to learn is often called personalisation in learning. Education research and practice have demonstrated that learning can be enhanced when the instructional process accommodates the various personalisation characteristics of students (Buch and Bartley 2002).

One of the theories of personalisation in learning is the theory of multiple intelligences as proposed by Gardner (1983; 1993; 2000); this theory provides eight different potential pathways of intellectual ability in learning, namely, visual/spatial intelligence (the ability to perceive the visual), verbal/linguistic intelligence (the ability to use words and language), logical/mathematical intelligence (the ability to use reason, logic and numbers), bodily/kinesthetic intelligence (the ability to control body movements and handle objects skillfully), musical/rhythmic intelligence (the ability to produce and appreciate music), interpersonal intelligence (the ability to relate to and understand others), intrapersonal intelligence (the ability to self-reflect and be aware of one's inner state of being) and naturalist intelligence (the ability to recognise plants and animals and other objects in nature). According to this theory, all human beings possess all these intelligences in varying degrees; these intelligences are located in different areas of the brain and can either work independently or together. The learning of an individual can accordingly be improved when the dominant intelligences are utilised in the learning processes.

Many studies integrate the multiple intelligences theory into teaching practices involving the use of ICT (Rosen, 1997; Cantau, 2000; Nelson, 1998). The Web-based learning environment and the LMS embody various instructional tools that can be used to address each of the eight ways of students’ learning activities representing each of the eight multiple intelligences. The animation integrated into the LMS is suitable for instructional strategies involving problem solving, investigation and experimentation; these can address the logical/mathematical needs of the students, whereas the chat room is the ideal means for synchronous collaboration and could be useful for addressing interpersonal needs. Other instructional tools, such as the availability of resources, the provision of graphics, images, audio elements, video clips, hypermedia and hypertext links, are suitable to address the instructional activities involving other multiple intelligences (Cantau, 2000).

In this study, we utilised the LMS and integrate the Bloom taxonomy higher order thinking skills and multiple intelligence characteristics dominant to the students to form a learning activity matrix. This instructional design was developed in the hope that it would be able to foster deeper understanding of the

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concept and will enable the students to think independently, skilfully and efficiently. In undertaking this study, the following question was asked: Does the MIWBL environment that integrates the multiple intelligence characteristics dominant to the students and the Bloom high order thinking skills to form the learning activity matrix produce better learning outcomes than that of the commonly used WCBL environment where delivery content does not take multiple intelligence preferences and high order thinking skills into consideration?

2. METHODOLOGY

2.1 The Web Instructional Design

To elicit the differences in terms of student learning outcomes between the commonly used WCBL and the experimental MIWBL, two Web pages with different instructional designs were developed and put online. One Web page utilised the instructional design of the WCBL while the other utilised the MIWBL. In both designs, the open source Moodle was used as a delivery platform.

2.1.1 The WBCL The design of the WBCL consisted of the following sequence of learning for each of the lessons:

a. Introductory information The students were required to browse through the introductory pages for information regarding the learning process involved and the role they should play.

b. Lesson objectives The lesson objectives were given before the presentation of the learning materials to guide the students in the learning process.

c. The content delivery The contents were broken down into smaller segments and the learning activities were structured from low-level to high and complex activities. The instructions were made as simple as possible to facilitate the students’ learning process.

d. Provision of examples Self-evaluation was also incorporated via probing problems and step-by-step answers to the problems were given to allow the students to gauge the level of their understanding and competency.

In this instructional design, the course content was delivered directly to the students. The students learned

by browsing through the course content and the learning activity tools available in the LMS, such as the asynchronous forum board, synchronous chat, links, quizzes etc. No specific instruction was given to them on when to use such tools in their learning sequence.

2.1.2 The MIWBL The instructional design of the MIWBL was based on the multiple intelligence characteristics of the sample. In order to elicit these characteristics, the Multiple Intelligence Inventory was administered to the sample in advance before the treatment. This inventory was adapted from Learning to Learn: Modules: Learning Styles: The Multiple Intelligent Inventory and consisted of 80 items with each item accompanied by a Likert scale ranging from 1-5, with 1 being “most disagree” and 5 being “most agree”. The analysis of the multiple intelligence inclination among the shows that the four most dominant multiple intelligence characteristics among the sample were the intrapersonal, the logical-mathematical, the naturalist and the interpersonal, whereas the non-dominant multiple intelligence characteristics were the visual/spatial, bodily/kinesthetic, musical and verbal/linguistics. Based on the dominant characteristics posed by the sample, the Bloom taxonomy multiple intelligence learning activity matrix was formulated. This matrix allowed the designed of the learning activity that conformed to the multiple intelligence characteristics and at the same time consisted of the Bloom taxonomy high order thinking skills. The learning activity matrix is shown in Table 1.

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Table 1. The bloom taxonomy multiple intelligence learning activity matrix

Bloom taxonomy high order thinking

skills

Multiple intelligences

Logical Mathematical

Interpersonal Intrapersonal Naturalist

Analysis - Exploratory - Producing a systematic plan

- Chat to obtain feedback from peers - Group discussion

- Undertake self-reflection towards problems

-Evaluate problems and self- needs in terms of the relationship with nature

Synthesis - Using a logic system to solve a problem - Provide reasons to choose an appropriate design - Conform to the measurement

- Discussion with various categories of people

- Use one’s own experience

- Using the available tools and techniques in nature to solve a problem

Evaluation - Evaluate the results/solutions in terms of criteria/ specifications and functions

- Obtain feedback about results/solutions from others

- Undertake reflection to improve results/ solutions

- Ensuring that products/ results/ solutions enhance the surrounding environment

The design instructional approach in the MIWBL thus took into consideration the learning activity in the matrix and involved the following sequence of learning:

a. Introductory information The students were first required to open and browse the introductory information pages that provided them with information and examples regarding the process of learning in the MIWBL approach and the role they should play to accomplish the content objectives of the course.

b. Lesson objectives The lesson objectives were given before the presentation of the learning materials to guide

the students in the learning process. c. The content delivery

The contents were broken down into smaller segments and the learning activities were structured from low-level to high and complex activities. The instructions were made as simple as possible to facilitate the students’ learning process.

d. Learning activities Unlike the WCBL approach, in this approach the student were given learning activities according to the Bloom taxonomy multiple intelligence learning matrix. This included the use of the synchronous chat tools that allowed the student to undertake online collaboration in small assigned groups of between 5-7 students, access to online resources to gather new information and concepts of the issues raised and the provision of animations that allowed them to manipulate parameters and observe their effects. Other LMS instructional tools that were also utilised were compatible with the learning activities in the above learning matrix.

e. Concept map construction At the end of the lesson, the students were required to construct the concept map. This

construction enabled them to develop a visual representation of newly constructed concepts of an idea or knowledge in such as way that all related concepts were organised and linked together with suitable descriptive terms. The links thus served as a visual way to identify relationships between the concepts that the students had acquired.

Figure 1 and Figure 2 depicted some of the learning activities that conformed to the bloom taxonomy multiple intelligence learning activity matrix.

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Figure 1. The animation that allowed the manipulation of various parameters. This activity would conform with students’ multiple intelligence characteristics and high order thinking skills.

Figure 2. Other learning activities that conformed to the students’ multiple intelligences and the Bloom taxonomy

learning activity matrix.

The sample of this study consisted of 103 students randomly chosen from a total of 456 enrolled in the fist year ZCT-104 Modern Physics course offered by the School of Physics, Universiti Sains Malaysia, for the first semester of the 2006/2007 academic session. The students were randomly divided into two separate groups (Group A and Group B), each treated with either the WCBL or the MIWBL approach. Lesson 1 was entitled Schrödinger Equation, Wave Function and Expectation Values while Lesson 2 was entitled Particle in a Box. The duration of each lesson treatment was one and a half hours and the course content for the CWBL and MIWBL approaches in both lessons were the same. To determine the learning outcomes from the treatments, the students were given the pre-test before the treatments and a similar post-test after the treatments. The pre-test and post-test questions and the marking scheme were validated by independent experts not involved in this study and a high consistency was achieved. A comparative analysis of their scores was conducted by means of a student t-test using a standard statistical package. The null hypothesis of

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this analysis was that there was no difference between the means of the two approaches under study pertaining to the learning outcomes as measured by the post-test scores.

3. RESULTS AND DISCUSSION

Table 2 shows the comparative analysis between the means of the pre-test scores of the WCBL and MIWBL approaches. It is clear that the students had no background knowledge of the topic to be delivered to them as the mean score in Lesson 1 for both sessions was zero. In Lesson 2, although the treatment group has recorded a non-zero pre-test score, it was small with no difference (p<0.05) from the nil score achieved by the control group. These results implied that both groups had no knowledge whatsoever of to the topics to be delivered and they were homogeneous in terms of the background knowledge before the treatments were carried out. Any difference that might have existed in background knowledge between the samples prior to the treatment would not have influenced the results of the comparative academic performances after the treatment as indicated in the post-test scores.

Table 2. Comparative analysis between the mean scores of the WCBL and MIWBL pre-tests for

Lesson 1 and Lesson 2 Group A Group B t-test Sig.

Control (N=55) WCBL

Treatment(N=48) MIWBL

Mean (std) %

Mean (std) %

Pre-Test (Lesson 1)

0.00 (0.00) 0.00 (0.00)

-

-

Treatment (N=55) MIWBL

Control (N=48) WCBL

Mean (std) %

Mean (std) %

Pre-Test (Lesson 2)

0.22 (1.62) 0.00(0.00)

-0.93

0.35

* p<0.05 The comparative academic performance analysis was carried out with a comparison between the means of the post-test scores between the WCBL and the MIWBL approaches. This analysis is shown in Table 3. As can been seen, there was a significant difference between the mean scores of the WCBL and MIWBL approaches in Lesson 1, with the MIWBL approach recording a significantly higher score. The score achieved when using the MIWBL in the LMS was almost four times better than that in the commonly used CWBL approach. Similar results were achieved in Lesson 2 where significant differences were observed between the two means with higher post-test scores being achieved by the students given the MIWBL treatment. Again in terms of the difference between the scores, the students following the MIWBL approach recorded scores almost four times better than those following the WCBL approach. These results are an indication that the MIWBL approach yielded better students’ academic performance, outperforming the commonly used WCBL approach when using the LMS as a course delivery mechanism.

Table 3. Post-test Comparative Analysis between the WCBL and MIWBL

Group A

Group B

T-test Sig.

WCBL (N=55)

MIWBL (N=48)

Mean (std) %

Mean (std) %

Post-Test (Lesson 1)

19.15 (8.92) 81.83 (11.56)

-31.00

0.00*

MIWBL (N=55)

WCBL (N=48)

Mean (std) %

Mean (std) %

Post -Test (Tutorial 2)

82.62(9.21) 24.67(11.28)

-28.69

0.00*

* p<0.05

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The enhancement of the students’ knowledge prior to and after the treatments between the two approaches is depicted in Figure 3 for Lesson 1. It is evident that both approaches produced considerable enhancement in terms of the knowledge constructed by the students. However, when the two approaches were compared, it was evident that the MIWBL approach yielded superior learning enhancement.

Figure 3. Enhancement of Learning Outcomes between CWBL (----) and MIWBL ( ) in Lesson 1

It is clear that the MIWBL approach brought about enhanced educational practices as far as the course delivery utilising the LMS was concerned. The inherent characteristic features of the MIWBL approach of learning in context, elaboration of knowledge through social interaction, an emphasis on meta-cognitive reasoning and self-directed learning that conformed to the dominant and preferred multiple intelligence dimensions with the Bloom taxonomy high order thinking skills can be easily supported by the instructional tools in the LMS leading to improved learning outcomes.

4. SUMMARY

This study elucidated the effectiveness of the MIWBL approach in terms of the students’ academic performances as compared to the commonly used WCBL approach. The results showed that the MIWBL approach has the ability to out-perform the WCBL approach in enhancing learning outcomes as indicated by the comparative analysis of the post-test scores. This implied that the students can performed better, after having acquired significant and enhance understanding of the concepts they are supposed to learn. The MIWBL approach, which is designed to conform to the multiple intelligences inclinations and preferences of the students with high level thinking skills activities, creates an engaging learning environment through social interaction, acquisition of skills in meta-cognitive reasoning and proficiency in problem solving skills. Even though the results achieved in this study cannot be generalised, but it is sufficient to indicate the need for in-depth study of an adaptive learning system which is designed and tailored to individual needs and learning capabilities. Specifically, detailed study is needed that looked into the adaptive learning system that incorporated learning designs that can foster higher order thinking skills among learners.

REFERENCES

Bloom, B.S. et al, 1956. Taxonomy of Educational Objectives: The classifications of Educational Goals. David McKay Company, New York.

Buch, K. and Bartley, S., 2002. Learning Style and Training Delivery Mode Preference. Journal of Workplace Learning. Vol. 14, No. 1, pp 5-10.

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Cantu, A., 2000. An Internet Based Multiple Intelligences Model for Teaching High School History. http://mcel.pacificu.edu/jahc/jahcII3/Cantu.PDF Cradler, J. et al, 2002. How does Technology Influence Student Learning? Learning and Leading with Technology, Vol.

29, No. 8, pp 46-49. Dori, Y.J., Tal, R.T. and Tsaushu, M., 2003. Teaching Biotechnology through Case Studies- Can We Improved Higher

Order Thinking Skills of Non science Majors? Science Education, Vol. 87, No. 6, pp 767-774. Gardner, H., 1983. Frames of Mind: The Theory of Multiple Intelligences. Basic, New York. Gardner, H.,1993. Multiple Intelligences: The Theory in Practice. Basic, New York. Gardner, H., 2000. Intelligence Reframed: Multiple Intelligences for the 21st Century. Basic, New York. Hanafi Atan et al., 2004. Problem-Based Learning (PBL) versus Content-Based Learning (PBL) in The Web-Based

Environment: An Analysis of Students’ Perceptions in the Learning Process. CD Proceedings of the 5th Asia-pacific Conference on Problem-Based Learning, Universiti Malaya, Kuala Lumpur, Malaysia, March 16-17.

Nelson, G., 1998. Internet/Web-Based Instruction and Multiple Intelligences. Educational Media International, Vol. 35, No. 2, pp 90-94.

Morgan,T., 1996. Using Technology to Enhance Learning: Changing The Chunks. Learning and Leading with Technology, Vol. 23, No. 50, pp 49-51.

Nichols, M., 2003. A Theory for E-Learning. Educational Technology & Society, Vol. 6, No. 2, pp 1-10. Available at http://ifets.ieee.org/periodical/6-2/1.html Rosen, D., 1997. Do Technology Based Lessons Meet the Needs of Student Learning Styles?

http://edweb.sdsu.edu/courses/edtec596r/students/Rosen/Rosen.html Rumetshofer, H. and Wöß, W., 2003. XML-based adaptation Framework for Psychological-Driven E-Learning

Systems. Educational Technology & Society, Vol. 6, No. 4, pp18-29. Available at http://ifets.ieee.org/periodical/6_3/4.pdf

Santally, M.I. and Senteni, A., 2005. Adaptation models for personalisation in Web-based learning environments. Malaysian Online Journal of Instructional Technology, Vol 2, No.1.

Yuretich, R.F., 2004. Measuring Skills in Large Introductory Science Classes. Journal of College Science Teaching, Vol. 33, No. 3, pp. 40-45.

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