The Effect of Anchored Instruction Models to Enhance

Understanding of Students Related Concept of Vector

Adam Malik

, Yudi Dirgantara

and Nur Muhammad

Department of Physics Education, UIN Sunan Gunung Djati Bandung, Jl A.H. Nasution No 105 Bandung, Indonesia

Keywords: Anchored instruction model, understanding, vector

Abstract: Observation result in MAN 1 Kuningan shows the low understanding of the concept of students. Therefore,

there is an effort to improve the understanding of the concept of physics subject on vector concept. This study

aims to determine the implementation of learning using the Anchored Instruction model and increased

understanding of student’ concept on vector concept. The method used in this research is pre experimental

design, with the design of one group pretest-posttest. The population of this study was students of class X IPA

MAN 1 Kuningan, the sample is selected by random sampling technique that is class X IPA 3 with the number

of 28 students. The activities of teacher and students are obtained through the observation sheet, and

enhancement of understanding of student concept is obtained from test essay. The results showed the activity

of teachers based on the observation sheet with an average percentage of 83% including good category and

average of students with the percentage of 74% including the medium category. Increased understanding of

students' concepts based on the average normalized gain of 0.71 including in the high category. The hypothesis

test was performed using a paired T-test obtained Tcount (25,946) > Ttable (2,052) which means Ho refused

and Ha accepted. Thus, Anchored Instruction model can be an alternative in enhancing of understanding of

students related concept of a vector.

1 INTRODUCTION

Physics is a subject that provides an opportunity for

students to be able to learn the symptoms and events

or natural phenomena by discussing, conducting

investigations, and working together to determine the

concept, principles and trained skills that can enable

students to grow independently (Pratama, Sudirman,

& Andriani, 2011). Understanding the concept of a

cognitive process that can provide interpretation, and

able to apply without having to connect with other

concepts. Understanding the concept of not just

knowing and merely recall the experience as well as

producing a concept that never learned, but it is a

gradual process. Understand is determining the

meaning of instructional messages, Including oral,

written, and graphic communication (Krathwohl,

2002).

Students' understanding of the concepts of physics

can be enhanced through the implementation of an

interactive model of meaningful learning and

structured so that the concepts presented are

embedded in student-term memory. One form of

meaningful learning model that is Anchored

Instruction (AI). Model Anchored Instruction has

characteristic that allows students actively involved

in learning to share their views with fellow students

and teachers (Love & Mary, 2004). Model AI also has

advantages compared with other models, including

students have a meaningful experience to solve a

problem, develop students' understanding in a

comprehensive manner so as to transfer knowledge in

a different context, with the kind of collaborative and

cooperative students, and learning to be more

effective (Blackhurts, Edward, & Timothy, 1996;

Crews, Biswas, Gildman, & Bransford, 1997; Donna,

Bird, & Brewer, 2004).

Some of the results of previous studies, the

application of the model Anchored Instruction (AI) in

learning to enhance the knowledge and abilities of

students. Various studies it such as AI can improve

mastery of concepts and learning outcomes (Sidik,

Ashari, & Maftukhin, 2016), mastery of concepts and

problem-solving skills (Hafizah, Hidayat, &

Muhardjito, 2014), problem-solving skills (Chen &

Howard, 2010; Shyu, 1997; Yulanda, 2014), learning

outcomes (Murtijah, Dwijanto, & Sukestiyarno,

2013), mathematical communication skills and self-

590

Malik, A., Dirgantara, Y. and Muhammad, N.

The Effect of Anchored Instruction Models to Enhance Understanding of Students Related Concept of Vector.

DOI: 10.5220/0010025200002917

In Proceedings of the 3rd International Conference on Social Sciences, Laws, Arts and Humanities (BINUS-JIC 2018), pages 590-594

ISBN: 978-989-758-515-9

concept (Saputra, 2012). In contrast to previous

studies, this research applying AI integrated with

laboratory activities to improve understanding of the

concept of students on the concept of the vector.

Learning the concept of vector rarely implemented

through laboratory activities. During this time the

teacher explained to students the concept of vector

analysis and mathematical methods through lectures

and question and answer.

2 METHODS

The method used in this study are pre-experimental

design with one-group pretest-posttest. This research

was conducted at the experimental class in the

without of a control group (Fraenkel H. H. H. Jack R,

Wallen, 2012). Type of data collected from this study

is qualitative and quantitative data. Qualitative data is

data about the activities of teachers and students in all

stages of learning with Anchored Instruction models

derived from observer comments on the observation

sheet. Quantitative data is data improved

understanding of the concept of the student after

application of Anchored Instruction models using

essay test and the percentage of the implementation

AI models derived from the observation sheet.

The population used in this study is an entire class

X IPA MAN 1 Kuningan 2017/2018 academic year

consisting of three classes. Samples were selected

using simple random sampling technique. After the

draw, the selected class is class X IPA 3 which has a

number of students were 28 people.

Stages Anchored Instruction models used in this

study consists of five stages: present a complex

problem; cooperate with others; solve problems;

discuss; and comparative perspective. The average

adherence to the activities of teachers and students

when applying Anchored Instruction models derived

from the percentage of the activities carried out at

each stage of the observation sheet. The percentage

after Purwanto then categorized according to criteria

consisting of: less than once (0%  54%); less (55%-

59%), sufficient (60%-75%); good (76%-85%); very

good (86%-100%) (Purwanto, 2008).

Indicators of conceptual understanding in this

study refer to Bloom's revised taxonomy consisting of

(1) interpreting; (2) exemplifying; (3) classifying; (4)

summarizing; (5) inferring; (6) comparing; (7)

explaining (Krathwohl, 2002). Increasing students'

understanding of concepts related to the vector

between before and after application of AI models

calculated using gain normalization (<g>) and

interpreted in accordance with the criteria Hake

(Hake, 1998). Before the hypothesis test, the

normality test and the results showed the data pretest

and posttest students' understanding of normal

distribution. Hypothesis testing is done using

parametric statistics are paired samples t-test to

determine the effect of the application of the

Anchored Instruction model on students

understanding.

3 RESULT AND DISCUSSION

3.1 Result

The average adherence to the activity of teachers at

the learning of applying the model of Anchored

Instruction in the whole learning based on data on the

observation sheet are presented in Table 1.

Based on Table 1 Teacher activity increased at

each stage of Anchored Instruction models. The

average the highest teacher activity obtained in step

cooperate with other that is equal to 85% with both

categories. The average teacher activity lowest in

comparative perspective stages amounting to 80% in

both categories. The average teacher activity at each

stage of the application of the overall Anchored

Instruction learning showed good category (83%).

Table 1: The average implementation teacher activity at all

learning.

No. Stages of

learning

model AI

Teacher learning

activities on

Ave-

rage

I II III

1 Preliminary 72 80 98 83

2 Present a

complex

Problem

78 80 93 84

3 Cooperate

with other

80 85 90 85

4 Solve

problems

75 78 93 82

5 Discuss 70 80 100 83

6 Comparative

Perspective

65 80 95 80

7 Close 70 82 93 82

Average 73 81 95 83

Interpretation Mode-

rate

Good Very

good

Good

The average enforceability of student activity at the

time of applying the model of AI in the whole meeting

based on data on the observation sheet are presented

in Table 2.

The Effect of Anchored Instruction Models to Enhance Understanding of Students Related Concept of Vector

591

Table 2: The average enforceability of student activity at all

learning.

No. Stages of

learning

model AI

Teacher learning

activities on

Ave-

rage

I II III

1 Preliminary 62 75 88

2 Present a

complex

Problem

65 80 80 75

3 Cooperate

with other

60 80 90 77

4 Solve

problems

60 80 80 73

5 Discuss 60 75 80 72

6 Comparative

Perspective

60 70 82 71

7 Close 62 77 87 75

Average 73 61 77 84

Interpretation Mode-

Rate

Mode-

rate

Good Good

Activities of students have increased at every stage of

the AI model. The average the highest student activity

obtained in step cooperate with other that is equal to

77% with both categories. Average of the lowest

student activity at the stage of comparative

perspective that is equal to 71% with the moderate

category. The average of student activity at each stage

of the application of the overall AI model meeting

showed enough category (74%).

The distribution of scores understanding students'

concept can be demonstrated by comparing the

average score pretest, posttest and normalized gain

<g> students on the vector concept.

Table 3: Score pretest, posttest and normalized gain

understanding of the concept of student

Score

Normalized

gain

Inter-

pretation

Pre-

Test

Post-

test

Amount 829 2211

0.71 High

Average 30 79

The improved understanding of the concept of the

student has applied to the concept vector AI models

included in the high category with an average

normalized gain of 0.70, the average value of pretest

30 and posttest average value of 79. Therefore, there

is an increased understanding concept of the student

after the application of the model AI on the concept

vectors.

The improved understanding concept of students

included in the low category does not exist. Students

who have increased understanding of the medium

category were as many as 11 people (39%). The

improved understanding concept of students included

in the high category there is 17 people (61%).

Data improvement on every indicator in the aspect

of students of understanding concept shown in Table

Table 4: The average score of the pretest, posttest and

normalized gain <g> for every indicator of understanding

concept

No. Indicator of

Under-

standing

concept

Value <g> Inter-

pretation

Pre-

test

Post-

test

1 Interpreting 38 85 0.76 High

2 Exempli-

fying

30 76 0.65 Mode-

ate

3 Classifying 36 80 0.69 Mode

rate

4 Summa-

rizing

27 80 0.73 High

5 Inferring 26 74 0.65 Mode-

rate

6 Comparing 30 90 0.86 High

7 Explaining 24 70 0.60 Mode-

rate

Average 30 79 0.71 High

Understanding of the concept of students in each

indicator has increased including medium and high

categories. Indicators comparing of understanding of

the concept is the highest increase with <g> of 0.86.

Indicator explaining of students of understanding is

the lowest increase with <g> of 0.60. The average

normalized gain of the entire indicator of

understanding aspects of students categorized as high

at 0.71.

Based on the data value calculation Lilliefors

pretest is Lcount (0.117) Ltable (0.161) with a 0.05

significance level, indicating that the data is normally

distributed pretest. Data posttest known Lcount

(0.159) Ltable (0.161) with a 0.05 significance level,

posttest data showed normal distribution. Based on

the results of hypothesis testing using a paired sample

T-test, Tcount = 25.964 values, at the 0.05

significance level the value Ttable = 2.052. From

these data indicate that the value of Tcount is greater

than the value Ttable. Results of the calculations and

the analysis showed that Ho refused and H1 accepted,

mean that the effect of applying the model anchored

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592

instruction in improving students' understanding of

the concept vector.

3.2 Discussion

Activities of teachers and students in general have

been steadily increasing in every meeting after the

model applied Anchored Instruction. The highest

stages of teacher and student activity occur in stages

cooperate with other. Students on stage cooperate

with other discussions and collaboration with

members of the group to plan and work on the

laboratory activity. This is supported by Isman

(Isman & Abdullah, 2014) which states students

cooperate and discuss with a friend's in the group, to

respect the opinion of others, help each other and are

more concerned with the interests of the group rather

than personal interests, so that the learning process

will be meaningful and appropriate plan set previous

Based on the analysis enforceability of the entire

meeting, it can be seen that the lowest stage of

activities undertaken by teachers and students is the

stage of comparative perspective. Students At this

stage the students to make conclusions from the

discussions with the group presented the results of

discussions in class and comment on the results of

student discussion. The low stage of comparative

perspective, due to several factors such as the student

who is not used in making inferences along with his

group, the lack of collecting data and information in

solving a problem to conclude learning. When in fact,

activity in this phase is an important stage because

students are expected to explore her abilities in

understanding the concepts of physics to solve the

problem given by the teacher. Simanjuntak

(Simajuntak, 2014) states that students who collect

more data and information can improve analytical

thinking skills to solve problems, such as

representing, comparing, classifying, and concluding.

The indicator comparing have normalized gain

value <g> the highest included in the high category.

This is because the students already understand when

making comparisons across the resultant vector using

mathematical and graphic analytical method to solve

a problem. This is in line with the results of research

conducted by (Yulanda, 2014) that the use of the

model anchored instruction affects the students'

mathematical problem-solving.

The indicator explaining has normalized gain

value <g> the lowest included in the medium

category. This is because the students have not been

optimal in developing an opinion when describing a

phenomenon that in accordance with the concept of

physics. In fact, according to Bloom understanding of

the concept is the ability to capture notions like being

able to disclose a material that is presented in a more

understandable form, is able to provide interpretation,

and able to apply (Anderson & Krathwohl, 2001).

Teachers should continue to train students to

understand every concept of the vector and its

application in daily life, so the ability to explain the

students can be improved (Saputra, 2012).

Overall results showed AI models can affect

students' increased understanding on the vector

concept. This reinforces previous research AI models

give positive results in a potential increase students

understand the concepts of the lessons (Chu, Kim, &

Cheong, 2011). Additionally, Lie (Lie, 2016) states

that the model anchored instruction can improve

students' problem-solving. Learning model that is

integrated with laboratory activities can improve

understanding of concepts, critical thinking skills,

creative thinking skills and communication skills of

the students (Malik, 2015; Malik et al., 2017;

Setiawan, Malik, Suhandi, & Permanasari, 2018).

4 CONCLUSIONS

We have successfully conducted research on the

influence of the model Anchored Instruction (AI) on

the students' understanding related to the vector

concept. The implementation each stage AI models

for teacher activity including good categories while

student activity including medium category. The

understanding of the concept of students categorized

high after applied AI models. Therefore, the AI model

considered appropriate models to be applied to other

physics concepts.

ACKNOWLEDGEMENTS

The author would like to thank the principals and

teachers of physics MAN 1 Kuningan has given

permission and help during the study. Thanks, are

also due to the chairman of the Center for Research

and Publishing UIN Sunan Gunung Djati Bandung

who has program writing class.

REFERENCES

Anderson, L. R., & Krathwohl, D. R. (2001). A Taxonomi

for Learning, Teaching and Assessing A Revision of

Bloom’s Taxonomi of Educational Objective. New

York: Longman.

The Effect of Anchored Instruction Models to Enhance Understanding of Students Related Concept of Vector

593

Blackhurts, Edward, A., & Timothy, E. M. E. (1996). Using

Anchored Instruction to Teach About Assistive

Technology. Focus on Autism and Other

Developmental Disabilies, 11, 131–141.

Chen, C., & Howard, B. (2010). Effect of Live Simulation

on Middle School Students’ Attitudes and Learning

toward Science. Educ. Technol. Soc., 13(1), 133–139.

Chu, S., Kim, N., & Cheong. (2011). Anchored Instruction

for Early Vocabulary Learning through Storybook

Reading: An Action Research. Int. J. Educ. Adm. Dev,

2(2), 48–62.

Crews, T. R., Biswas, G., Gildman, S., & Bransford.

(1997). Anchored Interactive Learning Environments.

International Journal of Artificial Intelligence in

Education, 8, 142–178.

Donna, B., Bird, M., & Brewer, S. (2004). Anchored

Instructio. Educ Technol Enclycl, 809–813.

Fraenkel H. H. H. Jack R, Wallen, N. E. (2012). How to

design and evaluate research in education. New York:

McGraw-Hill.

Hafizah, E., Hidayat, A., & Muhardjito. (2014). Pengaruh

Model Pembelajaran Anchored Instruction terhadap

Penguasaan Konsep dan Kemampuan Pemecahan

Masalah Fisika Siswa Kelas X,. Fisika Indonesia,

18(52), 8–12.

Hake, R. R. (1998). Interactive-engagement versus

traditional methods : A six-thousand-student survey of

mechanics test data for introductory physics courses

Interactive-engagement versus traditional methods : A

six-thousand-student survey of mechanics test data for

introduc. American Journal of Physics, 66(64), 64–74.

Isman, M. N., & Abdullah. (2014). Penggunaan Model

Pembelajaran Kooperatif Tipe Jigsaw untuk

Meningkatkan Kemampuan Berpikir Kreatif dan Soft

Skill Matematis Siswa SMA. Jurnal Matematika Dan

Pendidikan Matematika, 2(3), 39–53.

Krathwohl, D. R. (2002). A Revision of Bloom’s

Taxonomy: An Overview. Theory Into Pract, 41(4),

212–219.

Lie, H. (2016). Penerapan Model Pembelajaran Anchored

Instruction untuk Meningkatkan Kemampuan

Pemecahan Masalah Peserta Didik pada Materi Kalor.

J. Teach. Learn. Phys, 1(1), 13–18.

Love, & Mary, S. (2004). Multimodality of Learning

Throught Anchored Instruction. J. Adolesc. Adult Lit,

48(4), 300–310.

Malik, A. (2015). Model Problem Solving Laboratory to

Improve Comprehension the Concept of Students. In

Proc. Int. Semin. Math. Sci. Comput. Sci. Educ (pp. 43–

48).

Malik, A., Setiawan, A., Suhandi, A., Permanasari, A.,

Dirgantara, Y., Yuniarti, H., … Herminta. (2017).

Enhancing Communication Skill of Pre-Service

Physics Teacher Through Hot Lab Related to Electric

Circuit. J. Phys.: Conf. Ser,

953(1), 012017.

Murtijah, Dwijanto, & Sukestiyarno. (2013). Pembelajaran

Matematika Kelas V dengan Model Anchored

Instruction dengan Pendekatan Kontekstual. J Prim

Educ, 2(1), 148–155.

Pratama, A. A., Sudirman, & Andriani, N. (2011). Studi

Keterampilan Proses Sains pada Pembelajaran Fisika

Materi Getaran dan Gelombang di Kelas VIII SMP

Negeri 18 Palembang. Edumatica, 75, 100.

Purwanto, N. (2008). Prinsip-prinsip dan Teknik Evaluasi

Pengajaran. Bandung: PT Remaja Rosdakarya.

Saputra, E. (2012). Pengaruh Penggunaan Model

Anchored Instruction terhadap Peningkatan

Kemampuan Komunikasi Matematis dan Self-Concept

Siswa. Universitas Pendidikan Indonesia.

Setiawan, A., Malik, A., Suhandi, A., & Permanasari, A.

(2018). Effect of Higher Order Thinking Laboratory on

the Improvement of Critical and Creative Thinking

Skills. In IOP Conf. Ser. Mater. Sci. Eng (p. 012008).

Shyu, H. Y. C. (1997). Effect of Anchored Instruction

Enhancing Chinese Students Problem Solving Skill. Br.

J. Educ. Technol, 1, 57–69.

Sidik, A. I., Ashari, H., & Maftukhin, H. A. (2016).

Efektifitas Model Pembelajaran Anchored Instruction

(AI) terhadap Penguasaan Konsep Fisika dan Hasil

Belajar Siswa Kelas X SMA Muhammadiyah

Purworejo Tahun Pelajaran 2015/2016. Radiasi, 9(2).

Simajuntak, M. P. (2014). Efektifitas Model Problem Based

Learning terhadap Penguasaan Konsep Mahasiswa

pada Konsep Suhu dan Kalor. Jurnal Inapfi, 2(3), 126–

133.

Yulanda, S. (2014). Pengaruh Penggunaan Model

Anchored Instruction terhadap Peningkatan

Kemampuan Pemecahan Masalah Matematik pada

Siswa SMP Universitas Pendidikan Indonesia.

Universitas Pendidikan Indonesia.

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