Extent of ICT Integration in Science Based on SAMR Model

doi:10.21203/rs.3.rs-2008770/v1

Download PDF

Research Article

Extent of ICT Integration in Science Based on SAMR Model

https://doi.org/10.21203/rs.3.rs-2008770/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

This study presents the level of ICT integration of science teachers based on the SAMR model of Ruben R. Puentedura. The said model was put into the context of science education during the first semester of online distance learning school year 2021–2022. This study involves the participation of science teachers and students. The components of the SAMR model are used as an indicator of this study. There were 54 science teachers and 591 students who participated in this study; each respondent was given a researcher-made questionnaire which is validated by the experts and tested for internal consistency. The data gathered were analyzed using the following descriptive statistical tools: (a)Frequency Count and Percentage Distribution, (b) Mean and Standard Deviation, and (c) Analysis of Variance (ANOVA).

Based on the results Science teachers’ ICT integration is highly evident in the SAMR model’s Augmentation level. This is confirmed by the students. In the aforementioned model, augmentation is the second of four rungs. Science teachers utilized digital technology with improved functional change instead of traditional tools. It is in the enhancement of the Information and Communication Technology level but still needs to be upscaled to reach the transformational level where the use of ICT technology improves students' learning. The age and years of teaching experience of Science teachers have an impact on their ICT integration. Students’ perceptions of ICT integration in Science classes, on the other hand, are influenced by their curriculum, grade level, and school.

substitution

augmentation

modification

redefinition

ICT

Science education

These days, incorporating technology into the learning process opens new possibilities. Computers can benefit everyone; when utilized properly, they can help students learn more effectively. It enables teachers to offer training at any time, location, and pace, creating a highly adaptable learning environment. Computers can help students learn more effectively by allowing them to interact more with the topic or other people (Tuazon, 2019, Ramírez-Rueda et al., 2021, Offem & Anashie, 2021, Deshpande & Shesh, 2020).

Ruben R. Puentedura (2013) created the SAMR model to help librarians and educators thoroughly examine the levels at which they use ICT with their students and their educational practice. Furthermore, the SAMR model is utilized in this research to identify the ICT integration of science teachers during online distance learning.

Given the opportunity and resources that teachers have, they must be creative and utilize ICT as much as possible in education. Another thing is that if the teachers are using ICT, some use it as a direct substitute for learning materials, defeating the primary purpose of having ICT, especially in science education (Saritepeci, 2020, Ranjusha & Meera, 2022, ). Thus, the researchers conducted this study to determine the science teachers' ICT integration level if the redefinition stage is highly evident in their lessons.

This research provides insights to the science teachers out there to enhance and improve further their skills and competence in utilizing these educational technologies. For the students, it provides them with a wide range of learning experiences and further explores educational technology boundaries.

Review of Related Literature

1.1 ICT in Science Education

According to Abdullahi (2017), science education has its roots in the shift from an agrarian society to one dominated by and reliant on scientific and technological expertise. Several constraints are currently affecting teachers' motivation to use ICT in the classroom, including a lack of time to gain confidence and experience with the technology; limited access to reliable resources; a science curriculum overburdened with content assessments that do not require the use of technology; and a lack of subject-specific guidance for using ICT to support learning. Instead of transforming the prescribed curriculum and established pedagogy, ICT in the school science lab is driven by it. In summary, teachers tend to use ICT to support, enhance, and complement existing classroom practice rather than reshaping subject content, goals, or pedagogy. The teacher's motivation and commitment, on the other hand, are high, and the practice is gradually changing. Science appears to have had more success than other subjects in training teachers to use ICT in the classroom. (Abdullahi 2017).

Over the last two decades, a significant number of studies have analyzed the relationship between ICT and educational outcomes. These studies can be classified into quasi-experimental studies and empirical analyses of cognitive outcomes based on data sets such as PISA, PIRLS, and TIMMS in which the data represents the student population globally (Fernández-Gutiérrez, et al., 2020).

Today's science classrooms are not just about learning content and doing practical work by listening to a lecture or doing laboratory work; they are also about incorporating the digital world of multimedia instruction to help students grasp science concepts. Many software applications, such as Google and its sub-products, the Microsoft Office suite, could benefit from the active classroom as a foundation for web-based applications or software (Nugultham, 2018).

Gaille, (2019) says information technology offers other educational advantages, including 1) increased credibility for the teacher, 2) instant access to numerous resources, 3) the automation of boring material, 4) the development of a collaborative learning approach, 5) the easier teaching of core vocational skills, 6) the modernization of classrooms, 7) the centralization of needed data, 8) allowing students to work at their own pace, 9) the opportunity to learn in different ways, 10) increased motivation and 10) affordability.

In support of exploration and experimentation, ICT further allows teachers and students to observe or interact with simulations, animations, or phenomena in real ways that may be too dangerous, complex, or expensive for the school laboratory. It provides access to new forms of data previously unavailable.

1.2 The SAMR Model

The SAMR model is made up of four steps: Substitution, Augmentation, Modification, and Redefinition. Substitution and Augmentation are considered "enhancement" steps, while Modification and Redefinition are termed "transformation" steps. According to Puentedura (2006), the SAMR model is designed to be a tool to describe and categorize K-12 teachers' uses of classroom technology

The above-mentioned works of literature were important to this study since they provided the researcher with more information and a better comprehension of the topic. This study aims to find out how well science teachers use ICT in their online distance learning classes. The SAMR model does not account for the context in which technology integration happens (Hamilton, et. al 2016), thus the researcher tries to fill this gap by contextualizing the said model in the field of science education.

Statement of the Problem

This study determines the extent level of ICT integration by the Science teacher in Surigao City conducting online distance learning. Specifically, this sought to answer the following questions.

What is the profile of the teacher and student participants?
What is the level of ICT integration of the science teachers and perceived by the students based on the SAMR model?
Is there a significant difference in the level of ICT integration in relation to the SAMR model when grouped according to their profile?

2.1 Research model and procedure.

This study employed a descriptive research design using a survey technique. The design used is primarily to determine the level of ICT integration of science teachers. This is most appropriate since the researchers will only determine what level of ICT utilization they are in based on the SAMR model.

2.2 Research context and sample.

This research was conducted on all schools conducting online distance learning in Surigao City school year 2021-2022. Namely, Caraga Regional Science High School, Northeastern Mindanao College, St. Jude Thaddeus Institute of Technology, St. Paul University Surigao, Surigao del Norte National High School, and Systems Technology Institute Surigao. All the science teachers will be the respondents of this study.

Table 1 Distribution of Science teacher in Surigao City
School	N	%
Caraga Regional Science High School	9	16.70
North Eastern Mindanao College	3	5.60
St. Jude Thaddeus Institute of Technology	3	29.60
St. Paul University Surigao	9	16.70
Surigao del Norte National High School	29	53.70
STI Surigao	1	1.90
Total	54	100%

Research Respondents

Table 1 shows the distribution of respondents; the sampling technique used purposive sampling since we selected only the science teacher.

Table 2 shows the distribution sample of the students across the selected school for this study.

Table 2 Distribution of samples of student respondents
Schools	Grade Level						n	%
Schools	7	8	9	10	11	12	n	%
Caraga Regional Science High School	10	8	8	7	13	11	57	12%
North Eastern Mindanao College	4	6	5	8	10	7	40	8%
St. Jude Thaddeus Institute of Technology	1	1	1	1	1	1	6	1%
St. Paul University Surigao	9	10	13	12	23	17	84	17%
Surigao del Norte National High School	47	46	46	20	71	62	292	60%
STI Surigao					5	5	10	2%
Total	71	71	73	48	123	103	489	100%

2.3 Instrument used and their validation.

The instrument used to gather the data is the researcher-made questionnaire since the study is contextualized on the current delivery of instructions in science education. The first part is the profile of the respondents. This is crucial because it will evaluate their response in the second part of the questionnaire. The second part will focus on determining the level of ICT integration. The questionnaire has a version for the teacher and student. There is a slight change to the words for the appropriateness of the respondents. The second part of the questionnaire has 40 sets of questions. The sequence is randomized to prevent identifying the progression of the questions. Each item will be rated based on a four-point Likert-Type scale:

Table 3 Parametric scale of the research instrument
Scale	Parameter	Verbal Interpretation	Qualitative Description
4	3.25 - 4.00	Strongly Agree	High Evident
3	2.50 – 3.24	Agree	Evident
2	1.75 – 2.49	Disagree	Less Evident
1	1.00 - 1.74	Strongly Disagree	Not Evident

Validity. To ensure the research questionnaire's content validity, the contents of this will be based on the supporting related literature and studies. Furthermore, the questionnaire was validated internally and externally by the educators in line with their expertise.

Reliability. As to the reliability of the questionnaire, the researcher implements a pilot test method to determine the degree of the interrelationship among the items on a test. They are consistent and measure the same thing through Cronbach's alpha test. A generally accepted rule is that α of 0.6-0.7 indicates an acceptable level of reliability, and 0.8 or greater is a very good level (Griethuijsen et al., 2014, Ursachi et al., 2015 Daud et al., 2018,). However, values higher than 0.95 are not necessarily good since they might indicate redundancy (Ursachi et al., 2015). The result of the pilot run shows the α value of 0.93, which has high reliability.

3.4 Data analysis

Mean and standard deviation. These tools are used to describe the level of frequency of ICT integration that is present in the respondents

Analysis of the variance (ANOVA). These tools will be used to treat the significant difference and relationship in the level of ICT integration as to their profile.

Table 4

Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Substitution
During online class..			TEACHER			STUDENT
During online class..			M	SD	QD	M	SD	QD
1. Google forms, Kahoot, Mentimeter, and other tools are used in formative and summative assessments.			3.69	0.54	High Evident	3.34	0.81	High Evident
2. Still images or models are used to give a visual presentation of lessons.			3.61	0.56	High Evident	3.20	0.74	High Evident
3. Microsoft Word is used when making e-portfolios			3.56	0.63	High Evident	3.10	0.78	Evident
4. Concept or mind maps of the lessons are created using Microsoft Word.			3.52	0.54	High Evident	3.04	0.78	Evident
5. Projects are submitted through my email or Facebook messenger.			3.56	0.66	High Evident	3.15	0.85	Evident
6. Data are tabulated independently using e-tally sheets when the experiment is conducted.			3.26	0.56	High Evident	2.99	0.77	Evident
7. Evident-notes (Notes App, Google Doc, or Microsoft Word) are used for note-taking			3.33	0.70	High Evident	3.14	0.81	Evident
8. Pre-recorded lessons are used during the class.			3.11	0.74	Evident	2.86	0.91	Evident
9. Digital images are used for a virtual tour.			3.41	0.57	High Evident	3.05	0.82	Evident
10. Evident-tally sheets are used to record gathered data in conducting research studies.			3.30	0.74	High Evident	2.99	0.77	Evident
Average			3.44	0.63	High Evident	3.09	0.80	Evident
Note: The questions that are utilized in this table are those for the teacher. See Appendix A.
Legend
Scale	Parameters	Qualitative Description
4	3.25–4.00	High Evident
3	2.50–3.24	Evident
2	1.75–2.49	Less Evident
1	1.00–1.74	Not Evident

Table 5

Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Augmentation
During online class..			TEACHER			STUDENT
During online class..			M	SD	QD	M	SD	QD
1. Multimedia is integrated into Google forms, Kahoot, Mentimeter, etc. to enhance the students' understanding when taking formative and summative assessments.			3.52	0.57	High Evident	3.29	0.80	High Evident
2. The lesson has video clips to explain and support the visual presentation.			3.70	0.46	High Evident	3.31	0.76	High Evident
3. Evident-portfolios with interactive hyperlinks are created using Microsoft Word.			3.28	0.66	High Evident	2.95	0.81	Evident
4. Concept or mind maps are created with creative animation or voice-over of the lessons.			3.11	0.69	Evident	2.87	0.82	Evident
5. Projects are uploaded and compiled directly to an online folder for centralized feedback and improvement.			3.56	0.54	High Evident	3.15	0.75	Evident
6. MS Excel or Spreadsheet is used to present the data when the experiment is conducted.			3.50	0.61	High Evident	3.01	0.78	Evident
7. Multimedia like pictures, videos, etc. is added to e-notes (Notes App, Google Doc, or Microsoft Word).			3.54	0.61	High Evident	3.22	0.76	High Evident
8. Video lectures related to the lesson from other speakers are used during the class.			3.56	0.57	High Evident	3.23	0.74	High Evident
9. Video clips are used for a virtual tour.			3.35	0.65	High Evident	3.01	0.82	Evident
10. MS Excel or Spreadsheet is used to generate graphs to present the gathered data in a research study.			3.59	0.66	High Evident	3.04	0.76	Evident
Average			3.47	0.60	High Evident	3.11	0.78	Evident
Note: The questions that are utilized in this table are those for the teacher.
Legend
Scale	Parameters	Qualitative Description
4	3.25–4.00	High Evident
3	2.50–3.24	Evident
2	1.75–2.49	Less Evident
1	1.00–1.74	Not Evident
Table 6 Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Modification
During online class..			TEACHER			STUDENT
During online class..			M	SD	QD	M	SD	QD
1. Google forms, Kahoot, Mentimeter, etc. always show the scores and feedback after the formative and summative assessments.			3.48	0.61	High Evident	3.11	0.80	Evident
2. Augmented reality or any live 3D enhancements are applied to enhance the visuals of the lessons.			3.06	0.74	Evident	2.77	0.89	Evident
3. Evident-portfolios are created using google sites/blogsites.			3.26	0.65	High Evident	3.01	0.76	Evident
4. Active discussions thru group chats/blogs have been implemented while making concept or mind maps.			3.44	0.57	High Evident	3.07	0.75	Evident
5. Projects are submitted using Google Classroom or other LMS for automated monitoring.			3.61	0.56	High Evident	3.32	0.83	High Evident
6. Class data of the experiment are posted on an online platform to see the real-time graphs and charts.			3.20	0.60	High Evident	2.98	0.82	Evident
7. Annotation of the class eBooks, e-handouts, or e-notes (Notes App, Google Doc, or Microsoft Word) is done collaboratively.			3.28	0.66	High Evident	3.22	0.74	High Evident
8. Joining an online course related to the lesson is encouraged to the students.			3.50	0.58	High Evident	3.27	0.83	High Evident
9. Google Earth is used for a virtual tour.			2.70	0.92	Evident	2.60	0.99	Evident
10. Sending surveys using hyperlinks to community members and locals is used to gather data in a research study.			3.33	0.67	High Evident	3.11	0.78	Evident
Average			3.29	0.66	High Evident	3.05	0.82	Evident
Note: The questions that are utilized in this table are those for the teacher.
Legend
Scale	Parameters	Qualitative Description
4	3.25–4.00	High Evident
3	2.50–3.24	Evident
2	1.75–2.49	Less Evident
1	1.00–1.74	Not Evident

Table 7

Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Redefinition
During online class..							TEACHER					STUDENT
During online class..							M		SD	QD		M		SD		QD
1. Active collaboration in Google Forms, Kahoot, Mentimeter, etc. is implemented in making questionnaires that serve as review material.							3.46		0.61	High Evident		3.18		0.77		Evident
2. Virtual reality is used for the immersive content of the lessons.							3.04		0.70	Evident		2.86		0.94		Evident
3. Evident-portfolios are peer-reviewed or evaluated by the students on google sites or any blog sites in the comment section.							3.17		0.77	Evident		2.91		0.82		Evident
4. The class collaboratively contributed to the concept or mind map for the entire lesson through an active online platform.							3.39		0.56	High Evident		3.09		0.73		Evident
5. Projects are submitted using Google Classroom or other LMS and peer-reviewed or evaluated by the students in the comment section							3.56		0.60	High Evident		3.09		0.84		Evident
6. The result of the experimentation is shared-screen in the class for discussion.							3.30		0.66	High Evident		3.11		0.78		Evident
7. The class actively collaborates on class notes and annotates them on an online platform.							3.30		0.69	High Evident		3.10		0.79		Evident
8. Participating and giving feedback in the comment section of Massive Open Online Courses (EdX, Coursera, Khan Academy, Canva) are encouraged to the students.							3.11		0.79	Evident		3.03		0.80		Evident
9. Virtual reality is used for a virtual tour.							2.94		0.71	Evident		2.79		0.90		Evident
10. Posting surveys online to a global audience is used to gather data in a research study.							3.22		0.69	High Evident		3.07		0.80		Evident
Average							3.25		0.68	High Evident		3.02		0.82		Evident
Note: The questions that are utilized in this table are those for the teacher.
Legend
Scale		Parameters			Qualitative Description
4		3.25–4.00			High Evident
3		2.50–3.24			Evident
2		1.75–2.49			Less Evident
1		1.00–1.74			Not Evident
Table 8 Summary Comparison of ICT Integration of Science Teachers and Perceived by the Students Based on SAMR Model
				TEACHER							STUDENT
				M		SD		QD			M		SD		QD
Substitution				3.44		0.63		High Evident			3.09		0.80		Evident
Augmentation				3.47		0.60		High Evident			3.11		0.78		Evident
Modification				3.29		0.66		High Evident			3.05		0.82		Evident
Redefinition				3.25		0.68		High Evident			3.02		0.82		Evident
Average				3.36		0.64		High Evident			3.07		0.81		Evident
Legend
Scale	Parameters		Qualitative Description
4	3.25–4.00		High Evident
3	2.50–3.24		Evident
2	1.75–2.49		Less Evident
1	1.00–1.74		Not Evident

Table 8 Summary Comparison of ICT Integration of Science Teachers and Perceived by the Students Based on SAMR Model, shows that both teacher and student has high mean in terms of Augmentation, likewise in terms of Redefinition shows lowest mean.

Table 9

Significant Difference in the Level of ICT Integration of Teachers in Relation to SAMR Model as their Profiles
Profiles	Variable	f	p-value	Remark
Sex	Substitution	1.51	0.225	Not significant
	Augmentation	2.207	0.143	Not significant
	Modification	0.487	0.488	Not significant
	Redefinition	0.534	0.468	Not significant
Age	Substitution	3.204	0.006	Significant
	Augmentation	1.958	0.074	Not significant
	Modification	2.682	0.017	Significant
	Redefinition	2.387	0.031	Significant
Years in teaching	Substitution	3.761	0.001	Significant
	Augmentation	3.189	0.003	Significant
	Modification	1.907	0.066	Not significant
	Redefinition	2.549	0.014	Significant
Number of ICT trainings	Substitution	1.381	0.254	Not significant
	Augmentation	1.41	0.245	Not significant
	Modification	1.599	0.189	Not significant
	Redefinition	2.166	0.087	Not significant
Highest educational attainment	Substitution	0.607	0.66	Not significant
	Augmentation	0.828	0.514	Not significant
	Modification	0.634	0.641	Not significant
	Redefinition	0.714	0.587	Not significant
Schools	Substitution	1.442	0.226	Not significant
	Augmentation	2.375	0.053	Not significant
	Modification	1.687	0.156	Not significant
	Redefinition	1.945	0.104	Not significant
Note. The difference is significant when p-value is less than 0.05 significance level

Table 10

Significant Difference in the Perceived Level of ICT Integration of Students in Relation to SAMR model as their Profile
Profiles	Variable	f	p-value	Remark
Sex	Substitution	1.027	0.311	Not significant
	Augmentation	2.651	0.104	Not significant
	Modification	2.137	0.144	Not significant
	Redefinition	1.317	0.252	Not significant
Grade level	Substitution	2.272	0.046	Significant
	Augmentation	2.529	0.028	Significant
	Modification	2.102	0.064	Not significant
	Redefinition	2.412	0.035	Significant
Curriculum	Substitution	4.097	0.017	Significant
	Augmentation	5.612	0.004	Significant
	Modification	4.734	0.009	Significant
	Redefinition	5.565	0.004	Significant
School	Substitution	4.853	0.000	Significant
	Augmentation	5.816	0.000	Significant
	Modification	5.46	0.000	Significant
	Redefinition	8.684	0.000	Significant
Parents occupation	Substitution	1.529	0.084	Not significant
	Augmentation	0.986	0.470	Not significant
	Modification	1.329	0.174	Not significant
	Redefinition	1.342	0.166	Not significant
Note. The difference is significant when p-value is less than 0.05 significance level

Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Substitution

Table 4 Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Substitution, shows that they matched in terms of the highest mean "Google forms, Kahoot, Mentimeter, and other tools are used in formative and summative assessments." Similarities are also observed in the lowest mean with the statement "Pre-recorded lessons are used during the class.". This implies that teachers and students agreed on the construct that platform for the formative and summative assessment is observed; the same case also with pre-recorded lessons are not highly practiced. It means that substituting ICT with traditional educational technology is highly practiced.

The same result was also observed by the study conducted at the Makerere University (Lubega et al., 2017) that substitution of ICT is highly utilized in lectures. Similar reports also observed that the Google forms and other similar tools are being utilized rapidly in replacement of the traditional tools.

On the Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Augmentation

Table 5 Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Augmentation, shows that they matched in terms of the highest mean with the statement "The lesson has video clips to explain and support the visual presentation." Similarities are also observed in terms of the lowest mean with the statement, " Concept or mind maps are created with creative animation or voice-over of the lessons.". This implies that teachers and students agreed on the construct that video clips are used to augment the lessons, and concept mapping with media is not observed. This means that augmenting of ICT compared to substitution technology is highly practiced. Terada (2020), in his article, wrote that the Four tiers of online learning are equally important. The first two tiers for enhancing online learning, substitution and augmentation are equally practiced because augmentation cannot be practiced without the first one.

It implies that video clips are mainly used to augment the discussion since they can elaborate on the abstract concepts in science. The research of Savignano (2017) supports this stance that online learning video clips enhance the understanding of the visual presentation.

On the Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Modification

Table 6 Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Modification, shows that they matched in terms of the highest mean with the statement " Projects are submitted using Google Classroom or other LMS for automated monitoring." Similarities are also observed in terms of the lowest mean with the statement Google Earth is used for a virtual tour.". This implies that teachers and students agreed on the construct that learning management systems are used for automated monitoring of student progress and outputs, like that google earth is not widely utilized or known by the teacher and students. This means that Modification of ICT compared to Substitution and Augmentation is less practiced. Modification level includes changes in the students' learning tasks for their better understanding. Transforming assessment actions more frequently involved the enactment of student-centered practices through diversification of roles (Blundell et al., 2022).

On the Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Redefinition

Table 7 Comparison of ICT Integration of Science Teachers and Perceived by the Students in Terms of Redefinition, shows that they differ in terms of the highest mean, for the teacher " Projects are submitted using Google Classroom or other LMS and peer-reviewed or evaluated by the students in the comment section" and for the student "Active collaboration in Google Forms, Kahoot, Mentimeter, etc. is implemented in making questionnaires that serve as review material." Similarities are also observed in terms of the lowest mean with the statement "Virtual reality is used for a virtual tour.". This implies that teachers and students agreed that the platform for virtual reality is less likely to be used for virtual tours. This means that redefinition of ICT compared to Modification is less likely observed due to a lack of ICT devices or the idea that the latest and appropriate platform exist. Rahiem (2020) came up with research that some reasons both teachers and students experience device issues, internet connectivity, technology costs, lack of technology skills, and inadequate learning platforms which the process of redefining the ICT is slowed down.

On the Significant Difference in the Level of ICT Integration of Teachers in Relation to SAMR Model as their Profile

Table 9 Significant Difference in the Perceived Level of ICT Integration of Students in Relation to SAMR model as their Profile shows that Sex there was no significant difference among all variables such as Substitution (p = 0.225), Augmentation (p = 0.143), Modification (p = 0.488), and redefinition (p = 0.468) it means that in respect to the sex of teachers' level of ICT integration mentioned above did not affect on how far they utilized it in terms of the SAMR model.

In terms of Age, there was a significant difference in terms of Substitution (p = 0.006), Modification (p = 0.017), and redefinition (p = 0.031); young teachers were locally known as millennial educators. It was evident in the study by Daling (2018) showed that most of the teachers were still new in the teaching profession. It stresses that new teachers are efficient and effective in delivering ICT because they are exposed to modern trends. Millennial educators were equipped and exposed to ICT knowledge and skills. Daling (2018) added that seasoned teachers were more on traditional instruction, which significantly affected employing ICT in job performance.

As to Years Teaching Experience; there was a significant difference in terms of Substitution (p = 0.001), Augmentation (p = 0.003), redefinition (p = 0.014). However, in terms of the Modification (p = 0.066) statistically significant. According to Hartman et al. (2019), teacher experience influences teachers' adoption and integration of ICT significantly correlated with the actual use of technology. In addition, Lau and Sim (2017) conducted a study on ICT adoption among 250 Malaysian secondary school teachers. Their findings demonstrated that older teachers use computer technology in the classroom more frequently than younger teachers. The primary reason could be that the older teachers having rich experience in teaching, classroom management, and competence in using computers can easily integrate ICT into their teaching.

In the case of Number of ICT-Related Trainings, there is no significant difference in terms of number of ICT trainings as to Substitution (p = 0.254), Augmentation (p = 0.245), Modification (p = 0.189), redefinition (p = 0.087). This indicates that a number of ICT training does not affect the level of ICT integration. Several studies have found that ICT-related training programs improve teachers' computer skills, whether novice or seasoned. (Buabeng-Andoh, 2018), influencing teachers' attitudes towards computers and assisting teachers in reorganizing the task of technology and how new technology is used are significant in student learning.

As to Highest Educational Attainment, indicates that the highest educational attainment does not matter in terms of Substitution (p = 0.660), Augmentation (p = 0.514), Modification (p = 0.641), redefinition (p = 0.587). This indicates that a number of highest educational attainment does not affect the level of ICT integration.

School, shows that the school where the teacher is working is statistically not significant in terms of Substitution (p = 0.226), Augmentation (p = 0.053), Modification (p = 0.156), redefinition (p = 0.104). It clearly shows that the ICT integration of teachers as to the school where they are teaching does not matter. Ghavifekr (2015) also implies in his research that it does not matter in which school he is teaching for the ICT integration.

On the Significant Difference in the Perceived Level of ICT Integration of Students in Relation to SAMR model as their Profile

Table 10 Significant Difference in the Perceived Level of ICT Integration of Students in Relation to SAMR model as their Profile, Sex indicates that student's sex is not significant in terms of Substitution (p = 0.311), Augmentation (p = 0.104), Modification (p = 0.144), redefinition (p = 0.252). It means that with respect to the sex of students, the perceived level of ICT integration mentioned above did not affect how the teacher integrated ICT into the lessons. Bennett and Saunders (2019) have the same view that the level of ICT integration with the SAMR model as sex indicates that the students’ sex is not significant in terms of substitution.

As to the Grade Level shows that student grade level is statistically significant in terms of Substitution (p = 0.046), Augmentation (p = 0.028), and Redefinition (p = 0.035). However, in terms of Modification (p = 0.064) is not significant. It clearly shows that students' perceived level of ICT integration as to their grade level matters. Grade level plays an important role in classroom ICT utilization. As the student grade level progress, the topic becomes more complex and abstract; thus, ICT utilization is highly required. One of the possible reasons why to Modification stage is not significant due to the limited time preparation of the teachers such as preparing an automatic feedbacks system on the platform for the students to regulate their learnings Castro (2018) in which the students were not able to perceive this in their lessons.

In the case of Curriculum, it indicates significant differences in terms of Substitution (p = 0.017), Augmentation (p = 0.004), Modification (p = 0.009), redefinition (p = 0.004). It means that students' placements in curriculum matters such as science class and regular classes since the delivery of instruction may differ due to the nature of the group of students. Students in regular class may need more examples and things to augment the lesson for them to grasp the topic. Stiliana Milkova (n.d) in her research on teaching and learning wrote that the nature of the regular class and the delivery of instructions differ due to differences in the ability of the students.

In terms of School indicates that in terms of Substitution (p = < 0.05), Augmentation (p = < 0.05), Modification (p = < 0.05), redefinition (p = < 0.05). It clearly shows that the schools play an important avenue in learning, especially in the availability of resources, as they can influence the teaching strategy of the teachers. The research of Drexel University School of Education (n.d) also came up with this view in 2015 that the availability of resources in the school plays an important role in integrating ICT into online learning.

In the case of Parents Occupation, indicates no significant values as to Substitution (p = 0.084), Augmentation (p = 0.470), Modification (p = 0.174), redefinition (p = 0.166). Students' parents' occupations did not really matter as to how they perceived the ICT integration of the teacher since it is thought to be that the parents’ occupation affects the accessibility of the students to gadgets. A case study during covid-19 in rural Indonesia shows that the parent’s occupation really matters in the ICT integration because many parents do not afford the gadgets for their children (Lase et al., 2021).

In the light of the findings, the following conclusions were drawn:

ICT integration of science teachers is affected by the three constructs such as perceived technological knowledge, teachers' knowledge of technology, and perceived knowledge for integrating technology directly influencing teachers' ICT integration, except in pedagogical practices. Teaching experience and class size were found to be significantly related to the teachers' use of technology. The findings of this study will aid in the development of professional training to assist instructors in integrating technology into their classrooms, specifically by improving their ICT pedagogical practices (Ifinedo et al., 2020).

Limitation

This study aims to determine the extent of the ICT integration of the science teachers during online distance learning using the SAMR model of Puentedura (2009). Furthermore, this study utilized a questionnaire that will determine their practices based on the scale presented on the materials, other practices of science integration may not have been put into consideration since only ten common practices in ICT integration are being considered and they are modified progressively to fit into the criteria of each model.

Future research

Future researchers can re-evaluate this study after a certain period to determine if there are changes in the level of ICT integration of the teachers. Also, the study can be contextualized into different subject areas.

- Ethical statement

The researcher will ask permission from the School's Principal through a letter that he will conduct survey as part of the study to determine the teachers' level of ICT integration. Once the principal approves the permission, the researcher will ask permission from the respondents to respond to the survey questionnaire. There were ethics to be considered for conducting this study. The participants of this were vital parts of gathering and evaluating the data needed. The researchers will briefly explain to the respondent the purpose of this study concisely to be aware of what they are getting into. It will clarify that their participation was voluntary, and they could withdraw from this without any penalty. All the data will be collected from the participants will be treated with confidentiality and respect.

- Consent statement

By answering this survey, you consent to participate in this research voluntarily and agree with the Data Privacy Act of 2012 (RA 10173). All the information that will be collected from you will be stored for a limited duration. Rest assured that this data will be kept safe and secured; only the designated person will be able to access this information.

Data availability statements

The data that support the findings of this study are available from the corresponding author upon request. https://bit.ly/3QZAFEB

Disclosure of potential conflicts of interest

The authors have no conflicts of interest to declare. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report. We certify that the submission is original work and is not under review at any other publication.

Abdullahi, H. (2017). The role of ICT in teaching science education in schools. Journal of Educational and Social Research, 3(9), doi: https://doi.org/10.5901/jesr.2017. v3n9p127
Bennett, J. A., & Saunders, C. P. (2019). A virtual tour of the cell: Impact of virtual reality on student learning and engagement in the stem classroom. Journal of Microbiology & Biology Education, 20(2), doi: https://doi.org/10.1128/jmbe.v20i2.1658
Blundell, C. N., Mukherjee, M., & Nykvist, S. (2022). A scoping review of the application of the SAMR model in research. Computers and Education Open, 3, 100093. https://doi.org/10.1016/j.caeo.2022.100093
Buabeng-Andoh, C. (2018). Factors influencing teachers’ adoption and integration of information and communication technology into teaching: A review of the literature. Factors Influencing Teachers’ Adoption and Integration of Information and Communication Technology into Teaching: A Review of the Literature, 8(1), 136–155. https://files.eric.ed.gov/fulltext/EJ1084227.pdf
Castro, S. (2018). Google forms quizzes and substitution, augmentation, modification, and redefinition (SAMR) model integration. Issues and Trends in Educational Technology, 6(2), doi: https://doi.org/10.2458/azu_ itet _v6i2_castro
Daling, R. (2018). Secondary school teachers’ competency in information and communication technology. International Journal of Education and Research, 5(11), 117–122. Retrieved from https://www.ijern.com/journal/2018/Nove mber-2018/12.pdf on September 28, 2021
Daud, K. A. M., Khidzir, N. Z., Ismail, A. R., & Abdullah, F. A. (2018). Validity and reliability of instrument to measure social media skills among small and medium entrepreneurs at Pengkalan Datu River. International Journal of Development and Sustainability (IJDS), 7(3), 1026–1037. Retrieved from https://isdsnet.com/ijds-v7n3-15.pdf on October 25, 2021
Deshpande, S., & Shesh, A. (2020). Blended Learning and Analysis of Factors Affecting the Use of ICT in Education. Advances in Intelligent Systems and Computing, 311–324. https://doi.org/10.1007/978-981-15-4851-2_33
Drexel University School of Education (2022). (n.d.). How to integrate technology in the classroom. Drexel University. Retrieved from https://drexel.edu/soe/resources/student -teaching/advice/how-to-use-technology-in-the-classroom /on May 25,
Fernández-Gutiérrez, M., Gimenez, G., & Calero, J. (2020). Is the use of ICT in education leading to higher student outcomes? Analysis from the Spanish Autonomous Communities. Computers & Education, 157(1), 103969. https://doi.org/10.1016/j.compedu.2020.103969
Gaille, B. (2019). 23 Advantages and Disadvantages of Technology in Education. BrandonGaille.Com. Retrieved from https://brandongaille.com/23-advantages-disadvanta ges-technology-education/ on June 9, 2022
Ghavifekr, S., Kunjappan, T., Ramasamy, L., & Anthony, A. (2016). Teaching and learning with ict tools: issues and challenges from teachers' perceptions. Malaysian Online Journal of Educational Technology, 4, 38–57. Retrieved from https://files.eric.ed.gov/fulltext/EJ1096028.pdf on November 7, 2022
Griethuijsen, V., van Eijck, R. A. L. F., Haste, M. W., den Brok, H., Skinner, P. J., Mansour, N. C., Gencer, N. S., A., & BouJaoude, S. (2014). Global patterns in students’ views of science and interest in science. Research in Science Education, 45(4), 581–603. doi:https://doi.org/10.1007/s11165-014-9438-6
Hamilton, E. R., Rosenberg, J. M., & Akcaoglu, M. (2016). The substitution augmentation modification redefinition (SAMR) model: a critical review and suggestions for its use. TechTrends, 60(5), 433–441. doi:https://doi.org/10.1007/s11528-016-0091-y
Hartman, R. J., Townsend, M. B., & Jackson, M. (2019). Educators’ perceptions of technology integration into the classroom: a descriptive case study. Journal of Research in Innovative Teaching & Learning, 12(3), 236–249. doi:10.1108/jrit-03-2019-0044
Ifinedo, E., Rikala, J., & Hämäläinen, T. (2020). Factors affecting Nigerian teacher educators’ technology integration: Considering characteristics, knowledge constructs, ICT practices and beliefs. Computers & Education, 146, 103760. https://doi.org/10.1016/j. compedu.2019.103760
Lase, D., Zaluchu, S., Evident., Daeli, D. O., & Ndraha, A. (2020). Parents’ Perceptions of Distance Learning during Covid-19 Pandemic in Rural Indonesia. Journal of Education and Learning (EduLearn)https://doi.org/10.35542/osf.io /hz7t8
Milkova, S. (n.d.) (Ed.). (2022). Strategies for Effective Lesson Planning | CRLT. Center for Research on Learning & Teaching University of Michigan. Retrieved from https://crlt.umich.edu/gsis/p2_5 on May 25,
Nugultham, K. (2018). The advantages of Information and Communications and Technology (ICT) in Science Education. Proceedings of the International Conference on Science and Education and Technology 2018 (ISET 2018), 166, 19–24. doi:https://doi.org/10.2991/iset-18.2018.4
Offem, O. O., & Anashie, A. I. (2021). An overview of ICT in Education for National Transformation in 21st century and beyond. Unizik Journal of Educational Research and Policy Studies, 2, 271–280
Puentedura, R. (2013). Ruben R. Puentedura’s Weblog: SAMR: Moving from enhancement to transformation. Hippasus. Retrieved from http://www.hippasus.com/rrpweblog/archives/2013/05/29/SAMREnhancementToTransformation.pdf on October 9, 2021
Puentedura, R. (2006). Transformation, technology, and education. Hippasus Retrieved from http://hippasus.com/resources/tte/puentedura_tte.pdf "
Rahiem, M. D. H. (2020). Technological Barriers and Challenges in the Use of ICT during the COVID-19 Emergency Remote Learning. Universal Journal of Educational Research, 8(11B), 6124–6133. doi:https://doi.org/10.13189/ujer. 2020.082248
Ramírez-Rueda, M. D. C., Cózar-Gutiérrez, R., Roblizo Colmenero, M. J., & González-Calero, J. A. (2021). Towards a coordinated vision of ICT in education: A comparative analysis of Preschool and Primary Education teachers’ and parents’ perceptions. Teaching and Teacher Education, 100, 103300. https://doi.org/10.1016/j.tate.2021.103300
Ranjusha, A., & Meera, K. P. (2022). Role Of ICT in Science Education from Primary to Secondary School Education in Kerala. EPRA International Journal of Multidisciplinary Research (IJMR), 8(1), 37–101. http://www.eprajournals.net/index.php/IJMR/article/view/33/29
Saritepeci, M. (2020). Students’ and Parents’ Opinions on the Use of Digital Storytelling in Science Education. Technology, Knowledge and Learning, 26(1), 193–213. https://doi.org/10.1007/s10758-020-09440-y
Savignano, M. (2017). Educators’ perceptions of the substitution, augmentation, modification, redefinition model for technology integration. Retrieved from https://www.proquest.com/openview/20acff786525cebe 77a7c 0b1c61aa2ce/1?pq-origsite = gscholar&cbl = 18750 on May 24, 2022
Schoology (2020). (n.d.). SAMR model: A practical guide for edtech integration. Retrieved from https://www.schoology.com/blog/samr-model-practical-guide-edtech-integration on August 11,
Terada, Y. (2020). A powerful model for understanding good tech integration. Edutopia. Retrieved from https://www.edutopia.org/article/powerful-model-understanding-good-tech-integration on May 25, 2022
Tuazon, I. M. (2019). Implementation of DepEd computerization program (dcp) for the indigenous people. Asian Journal of Educational Research, 7(1), 1–14. Retrieved from http://multidisciplinaryjournals.com/wp-content/uploads /2019/02/Full-Paper-IMPLEMENTATION-OF-DepEd-COMPUTERIZ ATION-PROGRAM-DCP-FOR-THE.pdf on November 25, 2021
Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Economics and Finance, 20, 679–686. doi:https://doi.org/10.1016/s2212-5671(15)00123-9

Appendix A is not available with this version.

Download PDF

Version 1

posted

You are reading this latest preprint version

Extent of ICT Integration in Science Based on SAMR Model

Status:

Version 1

Abstract

Figures

Introduction And Review Of Literature

Method

Table 2

Results

Discussion

Conclusion, Limitations, And Future Research

Declarations

References

Appendix A

Status:

Version 1