The characteristics of gifted students' ecology

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Int. J. Mobile Learning and Organisation, Vol. 6, No. 1, 2012

The characteristics of gifted students’ ecology inquiries in ubiquitous learning activities Pi-Hsia Hung* Graduate Institute of Measurement and Statistics, National University of Tainan, Tainan, Taiwan Email: [email protected] *Corresponding author

Gwo-Jen Hwang Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taipei, Taiwan Email: [email protected]

I-Hua Lin Graduate Institute of Measurement and Statistics, National University of Tainan, Tainan, Taiwan Email: [email protected]

I-Hsiang Su Graduate Institute of Measurement and Statistics, National University of Tainan, Tainan, Taiwan Email: [email protected] Abstract: The purpose of this study was to investigate the differences on science inquiry competence and meta-cognitive strategies between the gifted and the average students in ubiquitous ecology learning activities. The participants were 27 gifted students and 63 average students from 4–5th grades. Two major instruments were developed for this investigation. The first was the criterion variable, Science Inquiry Literacy Assessment (SILA); the second was a questionnaire which consisted of three rating scales for ubiquitous ecology inquiry. All participants were required to respond to these two instruments after 8 weeks of inquiry. The results revealed that the gifted students performed significantly better than the average students in SILA and perceived usefulness of the mobile devices. The preliminary validities of perceived usefulness ratings also looked more promising for the gifted students than those for the average students. The meta-cognitive strategies for learning progress between two ability groups was not significant different.

Copyright © 2012 Inderscience Enterprises Ltd.

The characteristics of gifted students’ ecology inquiries

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Keywords: ubiquitous learning; science inquiry; gifted students; perceived usefulness; meta-cognitive strategies. Reference to this paper should be made as follows: Hung, P-H., Hwang, G-J., Lin, I-H. and Su, I-H. (2012) ‘The characteristics of gifted students’ ecology inquiries in ubiquitous learning activities’, Int. J. Mobile Learning and Organisation, Vol. 6, No. 1, pp.52–63. Biographical notes: Pi-Hsia Hung is currently a Professor in the Department of Education at the National University of Tainan, Taiwan. She earned her PhD in Educational Psychology, University of Minnesota, Minneapolis, specialising in educational measurement and online assessment. Her research interests include cognitive component analysis for large scale measurement, learning growth analysis, and online dynamic assessment. Gwo-Jen Hwang is currently a Chair Professor of National Taiwan University of Science and Technology. His research interests include mobile and ubiquitous learning, computer-assisted testing, expert systems and knowledge engineering. He has published more than 400 academic papers, including 150 papers in professional journals. Owing to his reputation in academic research and innovative inventions for e-learning, in both 2007 and 2010, he received the annual Most Outstanding Researcher Award from the National Science Council in Taiwan. I-Hua Lin is currently a Doctoral student in the Department of Education at the National University of Tainan. Her research interests include mobile and ubiquitous learning, web-based learning instructional designs and portfolio assessment. Her focus domain is in the natural science fields, especially in ecology-related subjects. I-Hsiang Su is currently a Doctoral student in the Department of Education at the National University of Tainan. His research interests include mobile and ubiquitous learning, web-based learning tools and measurement development.

1

Background and objectives

In the context of a changing world, science and technology play an important role at all levels of communities. Schools thus need to develop students in terms of their scientific knowledge and promote them to think critically (Nuangchalerm, 2010). The pedagogical aspects require inquiring minds in science in order for students to learn both scientific facts and creativity. Learning perspectives have also been considered as an important aspect of science education goals (Bell and Lederman, 2003). Science education has an important responsibility to provide students with individual experiences and promote positive attitudes towards science. The aim of school science is to enable students to observe their natural environment and to develop the skills required to understand and explain both themselves and their environment (Marx et al., 1994). In science education, inquiry-based learning allows students to learn by doing, is relied on Dewey’s school life and on that students learn how to solve problems by themselves (Dewey, 1966). This method is a complex but realistic process in which students use their prior knowledge and scientific theories to generate new understandings of science (Yoshina and Harada, 2007). The idea of teaching science using the inquiry

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method allows students to develop, explore, and experiment with their own concepts about science. In addition, inquiry-based learning can refer to diverse ways in which scientists study the natural world and propose explanations based on evidence derived from their work. It includes the activities of students in which they develop knowledge and understanding of scientific ideas, as well as an understanding of how scientists study the natural world (National Research Council, 1996). Inquiry teaching challenges science learning to develop new content knowledge, pedagogical techniques, and approaches to assessment and classroom management (Krajcik et al., 1999). It means that inquiry-based learning can open windows of opportunity for students to explore and understand the natural world by themselves. Observation is the process of gathering information about objects, events or processes in a careful and orderly way (Hwang et al., 2010). Success in science education not only depends on the students’ knowledge and understanding of environmental challenges, but also on impassioned participation in environmental conservation activities. Observation plays a fundamental role in students engaging in and caring about environmental issues. Teachers need to help students develop their science observation competence by designing cognition activities, in particular, for outdoor teaching, which provides an excellent opportunity for conducting such scientific observation activities (Chu et al., 2010). Problem-based learning is a model that organises learning around projects. It is definitely based on challenging questions or problems that involve students in design, problem-solving, decision making, or investigative activities; give students the opportunity to learn relatively autonomously (Marx et al., 1994; Jones et al., 1997). In reaching instructional goals, students’ perceptions of achievement, understanding of learning, studying habits and interactions with others in the teaching and learning environment are among the determining factors. When students are simultaneously involved in the execution of the same task and must achieve a common goal, there is a need to share ideas, to coordinate and to negotiate meanings. Researchers have indicated that shared goals enhance a positive interdependency between the collaborating students (Cohen, 1986; Johnson and Johnson, 1994); moreover, a positive interdependency exists when the participants of the group perceive that they cannot succeed unless the others do, and that they must coordinate their efforts with the efforts of the others to complete the task (Johnson and Johnson, 1994). Mobile phones, personal digital assistants (PDA), and laptops come standard with built-in wireless, encouraging learners to access the information network anywhere they happen to be (Hwang et al., 2009). Mobile devices have also become more popular as cognitive tools in science learning (Vogel et al., 2010; Hwang et al., 2011). With the advantages of portability and easy information access, mobile technologies are now used frequently in outdoor scientific investigation activities. In the current study, smartphones were used by the students to carry out ecology observation and scientific inquiry. Thus, the students’ perceptions of the usefulness of these mobile devices might be related to their inquiry performance (Hwang and Chang, 2011). Self-regulated students are those who are meta-cognitively, motivationally and behaviourally active participants in their own learning process (Zimmerman, 1986). These students have been described as confident, autonomous, inquisitive learners who employ meta-cognitive strategies to facilitate their learning (Zimmerman and MartinezPons, 1988; Risemberg and Zimmerman, 1992).


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In the framework of social cognitive theory, in order to be classified as a selfregulated learner, a student must use ‘specified strategies to achieve academic goals on the basis of self-efficacy perceptions’ (Zimmerman, 1989). Zimmerman and MartinezPons (1988) have indicated three components of self-regulation: 1

the behavioural aspect, such as the observable tactics used by students for enhancing learning

2

the cognitive aspect, such as the academic meaning of self-efficacy which represents students’ beliefs in their ability to learn

3

the affective aspect, such as the intrinsic motivation which represents students’ desire to learn, and their joy in learning.

Learning strategies have been found to be associated with academic performance. Students who are high achievers use more self-regulated learning strategies than low achievers, although these strategies may vary among students (Hung et al., 2010). The purpose of this study is to explore the characteristics of gifted students in ubiquitous science inquiry activities. The differences between gifted and average students might be good indicators for scaffolding average students’ learning design. The variables included were science inquiry competence, perceived usefulness of the mobile devices, and meta-cognitive strategies for learning progress. Two related research questions are listed below: 1

Are there differences between gifted and average students in science inquiry competence, their perceptions of the usefulness of the mobile devices, and their meta-cognitive strategies for learning progress?

2

Are there differences between gifted male and female students in science inquiry competence, their perceptions of the usefulness of the mobile devices, and their meta-cognitive strategies for learning progress?

2

Research design

Figure 1 presents the ubiquitous science inquiry learning model for this study. The inner cycle represents the online learning activities, while the outer cycle represents the group inquiry tasks. At the very beginning of the intervention, three periods (120 minutes) of anchored instruction were provided for all participants to help them become familiar with the learning aids. All participants were equipped with a smartphone which was used to search for information, and to record and submit data to accomplish the problem-based learning (PBL) tasks in the field. Then a three-hour trip to Chiku Wetland was arranged for the participants to observe and record the variables of the environment. The participants were asked to complete learning diaries on the website, based on what they had collected and learned. The ubiquitous PBL (UPBL) started with an inquiry problem after the students’ first field trip. They had taken some measurements and submitted their data by mobile device (Figure 2). Then, they worked on their inquiry plans. The students learned to reflect by writing a diary and via online discussion. Adaptive feedback was provided online to support the learning progress of the UPBL by the class teachers. After 8 weeks of learning, all participants responded to an inquiry questionnaire and completed a science inquiry competence assessment.

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Figure 1

The ubiquitous science inquiry learning model (see online version for colours)

Revised Inquiry Plan

Anchored Instruction

Reflection Discussion

Field Trip Measurement

Sharing

Inquiry Plan Trial

Figure 2

Measurement tasks for the ubiquitous ecology inquiry (see online version for colours) Smartphone

Data checking

QRcode

Biology Inquiry

measurement instruments

Measurement Tasks

Data submission

Notes & comments

information searching

2.1 Participants A total of 90 students were included in this study, of which 27 were gifted students from the 4th grade and 63 were average students from the 5th grade (see Table 1). The gifted sample was the focus group to explore the potential of UPBL effects for elementary school children. In this study, it is assumed that advanced learning technology will be profitable for all students. Moreover, the gifted group might help this study speed up the explorations; that is, it was assumed that using the gifted sample would help to detect promising intervention designs. Table 1

The frequency distribution for gifted and average students Gender

Group 4th grade (gifted)

Male

Female

Total

19

8

27

5th grade (average)

39

24

63

Total

58

32

90


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2.2 Online science inquiry literacy assessment (SILA) The SILA was developed to assess students’ science inquiry competence. There are totally 36 multiple choice items (Table 2). Three types of items are included in the SILA, namely observation (via multi-media), inference and experimental design. A sample item of inference is provided in Figure 3. The responses of 950 5th graders from southern Taiwan were calibrated using an item response theory (IRT) model. The item IRT difficulty parameters of SILA are classified into three levels, namely basic, proficient, and advanced. The average difficulty (p-value) is 0.54 and the internal consistency alpha is 0.63. Table 2

Test specifications for SILA

Content

Basic

Proficient

Advanced

Total

Observation

8

6

6

20

Inference

3

3

3

9

Experimental design

2

3

2

7

Total

13

12

11

36

Figure 3

A sample item of database inference for SILA (see online version for colours)

dissolved oxygen

pH

Question: There are 3 areas, A, B and C, in the ecology park. Jack recorded the

A

B

C

A

B

pH, dissolved oxygen and the number of species respectively. Which statement is correct for the relationship inference between the environment feature and the number of species based on the following charts.

A

B bird crab fish

C

1. The number of fishes in A area is largest because the pH is highest. 2. The number of fishes in B area is smallest because the dissolved oxygen is lowest. 3. The number of birds in C area is smallest because the dissolved oxygen is highest.

C

submit button

4. The magnitude of pH is an important factor for the number of the fish, birds and crabs.

2.3 Questionnaires of perceived usefulness and meta-cognitive strategies The inquiry questionnaire consisted of three rating scales for ubiquitous science inquiry, rating the perceived usefulness of the mobile devices (the smartphones and the database) and meta-cognitive strategies for learning progress. The number of items for each scale is provided in Table 3. For each rating scale, several strategies are proposed. The students were requested to rate the usefulness from 4 to 1 for each of the five strategies, including

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‘Using the smartphone for video and picture taking’, ‘Using the smartphone for note taking’, ‘Using the smartphone for information searching’, ‘Using the smartphone for data submitting’ and ‘Using the smartphone for measurement data searching (checking)’, as shown in Figure 4. Higher usefulness ratings represent more positive appreciation of or attitudes towards using the mobile devices. The meta-cognitive strategies were scored according to the pair comparison method. The key derived from experts’ consensus is that strategies 3 and 4 (i.e. making a plan and checking regularly) are better than 1 and 2 (i.e. teacher’s checking and doing my best). The items for this scale are also listed in Table 9. The alpha coefficients for the scales in Table 3 are around 0.70. Table 3

The item distribution of the three rating scales

Scales

Item

Usefulness ratings of the smartphones

5

Usefulness ratings of the database

5

Meta-cognitive strategies for learning progress

4

Total

14

Figure 4

Items for perceived usefulness of the smartphones (see online version for colours)

Perceived Usefulness of Smartphone Application How is the usefulness of each following Smartphone application for your UPBL?

Smartphone

1. Using the smartphone for video and picture taking. 2. Using the smartphone for note taking. 3. Using the smartphone for information searching. 4. Using the smartphone for data submitting. 5. Using the smartphone for measurement data searching (checking).

3

Results

3.1 The differences between the gifted and average students Generally speaking, most of the participants enjoyed using the mobile devices to record, take notes and photos, search for information, and submit or check the data. The results shown in Table 4 reveal that, except for meta-cognitive strategies, the gifted 4th graders performed better than the average 5th graders. The variances explained by ability group


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range from 7% to 25% (as shown in Table 5). The group difference in the perceived usefulness ratings of the database is especially large (η2 = .245). It was found that the gifted students were more inclined to data-based inquiry, while the average students might need more explicit guidance in applying the database for inquiry purposes. On the other hand, there was no difference between the gifted and average students in terms of their meta-cognitive strategies for learning progress. It is assumed that the students’ autonomous learning habits had not yet emerged and that they required more experience of meta-cognitive strategy practice to monitor their own learning. After conducting the 8-week intervention, it was found that the variables selected in this study were quite promising for detecting the UPBL discriminating effect from the differences between the groups. In other words, the performance of the gifted students will help us to set realistic standards of UPBL design for all students. Table 4

Contrasts of descriptive statistics for the four variables between the gifted and average students Gifted students (n = 27)

Variables

Average students (n = 63)

M

SD

M

SD

Science inquiry competence

27.19

5.59

23.45

7.06

Usefulness ratings of the smartphones

19.45

1.23

18.45

1.94


19.29

1.32

16.80

2.39

Meta-cognitive strategies for progress

5.16

2.46

5.20

2.99

Table 5

Summary of analysis of variance for the four variables between the gifted and average students (n = 90)

Variables Science Inquiry

VS

SS

df

MS

F

p

η2

5.846

.018

.066

6.847

.010

.071

28.928

.000

.245

.004

.951

.000

Between

257.25

1

257.25

Within

3625.42

89

44.01

20.51

1

20.51

Usefulness ratings of the mobile devices

Between Within

266.527

89

2.99


Between

126.76

1

126.76

Within

389.99

89

4.38

Meta-cognitive strategies for progress

Between

.031

1

.031

711.79

89

7.99

Within

3.2 The differences between gifted male and female students The contrasts of the descriptive statistics between the gifted male and female students for the four variables are provided in Table 6. Generally speaking, their performance was quite similar. The gender difference is not significant for any variable. The item-wise contrasts are provided in Table 7 to Table 9. The correlation coefficients between the items of the four variables and SILA are also included. For the gifted students, the correlation coefficient between the usefulness ratings of the smartphones and SILA is 0.51. The correlation coefficient between meta-cognitive strategies for learning progress and SILA is 0.30.

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Table 6

Contrasts in the descriptive statistics for the four variables between gifted male and female students (n = 27) Male (n = 19)

Variables

Female (n = 8)

M

SD

M

SD

Science inquiry competence

27.26

5.94

27.00

5.01

Usefulness ratings of the mobile devices

19.26

1.49

19.75

0.71


19.05

1.55

19.75

0.71

Meta-cognitive strategies for learning

5.47

2.89

5.50

0.93

Table 7

Contrasts in the item means of the usefulness ratings of the smartphones between gifted male and female students (n = 27) Male (n = 19) M

Female (n = 8) M

Correlation with SILA

1 Using the smartphone for video and picture taking

3.84

4.00

.36

2 Using the smartphone for note taking

3.79

3.88

.51**

3.84

3.88

.36

3.89

4.00

.22

3.89

4.00

.45*

19.26

19.75

.51**

Scale

Items

Usefulness ratings 3 Using the smartphone for information searching of mobile device 4 Using the smartphone for data submitting 5 Using the smartphone for measurement data searching Sum Notes: Table 8

*p < .05, **p < .01. Contrasts in the item means of the usefulness ratings of the database between gifted male and female students (n = 27)

Scale

Usefulness ratings of database

Sum

Male (n = 19) M

Female (n = 8) M

Correlation with SILA

1 Checking the agreement of measurement results

3.89

4.00

–.02

2 Investigating the characteristics of different areas

3.89

3.88

.08

3 Investigating the changing pattern for different times

3.74

3.88

.27

4 Using the plots or diagrams for investigating the changing pattern or relationship of measurement variables

3.84

4.00

.23

5 Using plots or diagrams for reports

3.68

4.00

–.25

19.05

19.75

.07

Items

The characteristics of gifted students’ ecology inquiries Table 9

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Contrasts in the item means of meta-cognitive strategies for learning progress between gifted male and female students (n = 27) Male (n = 19) M

Female (n = 8) M

Correlation with (SILA)

1 Asking the teacher to help me check

1.37

1.75

.10

2 Just working as hard as possible Meta-cognitive strategies for 3 Making a plan about tasks to do each week learning progress

1.16

.50

.33

1.53

1.50

.18

1.42

1.75

.30

5.47

5.50

.30

Scale

Items

4 Checking progress each week and revising plan as needed Sum Notes:

Key: 3, 4 > 1, 2.

The only meta-cognitive strategy item for which the male students scored higher than the female students was ‘Just working as hard as possible’. The experts rated this strategy as being less effective; however, the gifted female students thought this strategy was quite useful. The correlation coefficient between this item and SILA looks promising (0.33). Further studies are needed to take a detailed look at this aspect. The correlation coefficients between these three scales and SILA were not significant for the average students. The preliminary results suggest that these three scales are more valid for gifted students than for average students. The average students may need more specific guidance in using mobile devices as learning tools for inquiry purposes.

4

Conclusions

Ubiquitous science inquiry has been shown to have potential for enhancing meaningful learning in science education. We assume that the learning progress of gifted students will be a faster process for us to explore the critical factors of ubiquitous learning design. After the 8-week inquiry activity, all participants responded to the questionnaire and completed the assessment. The ubiquitous science inquiry rating scales developed in this study were linked closely to the students’ inquiries. The experimental results reveal that the gifted students performed significantly better than the average students in three aspects, but not for the meta-cognitive strategies for learning progress. The group difference for the usefulness ratings of the database is especially large. In other words, the gifted students are more inclined to data-based inquiry. We suspect that average students may need more inquiry experience to develop this disposition. There was no difference in the meta-cognitive strategies for learning progress between the gifted and average students. We assume that self-regulated learning habits may not yet have emerged for most 4th and 5th graders. Students may need more encouragement for meta-cognitive strategy practice to become effective learners. Via a limited intervention (the 8-week inquiry activity), the differences between ability groups demonstrate that the variables selected in this study are quite promising. The discrepancies highlight the critical supports needed for UPBL design. The performance of the gifted 4th grade students will also help us set up realistic standards for average students. The correlation coefficient between science inquiry competence and

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usefulness ratings for smartphones is around 0.51 for the gifted children but not significant for the average students. Therefore, it would also be important to investigate the different ways of using mobile devices between gifted and average students. Since the correlation coefficient is unstable for small sample sizes, a longer scale and larger sample size are needed for further studies.

Acknowledgements The authors would like to thank Mr. Bahtijar Vogel and Prof. Marcelo Milrad in Linnaeus University, Sweden, for providing the technical support to this study. This project is funded by the National Science Council of the Republic of China under contract numbers NSC 99-2511-S-011-011-MY3 and NSC 100-2631-S-011-003.

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