IMPLEMENTATION OF THE TPACK FRAMEWORK TO MEASURE INTEGRATION OF TECHNOLOGY, PEDAGOGY AND THE CONTENT OF LECTURERS IN MATHEMATICS EDUCATION

One of the obstacles using technology is the lack of teacher understanding of technology, therefore this study aims to determine the understanding of lecturers of mathematics education on the integration of technology in learning using the TPACK (Technological, Pedagogical, Content Knowledge) framework, a few of research that applying TPACK in universities. Furthermore, the both effect of gender and age of teaching on TPACK were analyzed on TPACK using analysis of variance (ANOVA). The results of this study are Power point applications are technologies that are widely used by mathematics education lecturers by 40.9%. PCK, PK and CK components have a strong positive effect on TPACK perceptions of mathematics education lecturers. The average value of TPACK components is TK 3.95; CK 4.01; PK 4.08; 4.02 PCK; TCK 4.04; TPK 4.02; TPACK 3.96. For an in-depth analysis of gender and age of teaching factors on the TPACK component. This study found that gender and duration of teaching was no significant influence between the understanding of mathematics education lecturers and the seven components of TPACK.


INTRODUCTION
The emergence of Information and Communication Technology (ICT) has an impact on several things, including the field of education. Mathematics education is also required to make changes according to the development of ICT (Haapasalo, 2017). This change is marked by the use of technology in the learning process such as learning media.
The use of this technology is expected to increase the effectiveness of learning. Eng (2005) explains that the use of ICT can have a positive effect on student learning. Keong,

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Implementation of the tpack framework to measure integration of technology, pedagogy and the content of … Nindiasari, Restina, Pamungkas Horani, & Daniel (2005) state that learning mathematics using ICT can make learning more effective and provide increased student ability to understand basic concepts. Andreou (2017) adds that the use of technology makes students increase in problem-solving abilities, critical thinking, and comprehensive understanding of mathematical concepts.
One of the determining factors for the successful use of technology in learning is the understanding of technology teachers or users (Englund, Olofsson, & Price, 2017). Teachers must have expertise in the use of technology to support learning and improve student understanding (Otero et al., 2005). However, there are still obstacles to the understanding of teachers in using this technology, including the limited understanding and mastery of technology and teachers' perceptions of innovative learning techniques (Andreou, 2017).
The existence of these obstacles encourages various studies to evaluate teacher understanding in integrating ICT. The evaluation method used can use the Technological, Pedagogical, Content, Knowledge (TPACK) framework. Koehler and Mishra (2009) explain that TPACK is the basis for integration between the components of content knowledge (CK), pedagogical knowledge (PK), and technological knowledge (TK) as seen in Figure 1. In general, CK is described as the teaching ability of the material invited. PK is the teacher's ability to know how to teach appropriately. Meanwhile, TK is the ability of a teacher to use various kinds of technology sources in learning.

Figure 1. TPACK Framework
In addition to the three main components, there are areas of intersection between these components, namely PCK (pedagogical content knowledge), TPK (technological pedagogical knowledge), and TCK (technological content knowledge), while TPACK (technological pedagogical content knowledge) is the middle point.  state that these 7 components have a positive and significant relationship.
Research using the TPACK framework has been carried out in several ways. One of them is TPACK which is used to explore the use of ICT in mathematics learning (Chai, Koh, Tsai, & Tan, 2011;Jang & Tsai, 2012;Liang & Luo, 2016 Benson & Ward (2013) conclude that every professor has a different understanding of the use of technology and a professor whose understanding is good in pedagogical knowledge will tend to show TPACK integration. However, this research is still qualitative in nature and limited to individuals without involving the influence of gender and length of teaching.
Thus, research on the mastery of TPACK in college teachers and its relationship with gender and length of teaching still needs to be done, so this research is carried out in order to fill this gap.

METHODS
This research is a quantitative correlational study which aims to determine the understanding of mathematics education lecturers in the use of learning technology with the TPACK framework approach and to see the relationship between gender and length of teaching on the TPACK ability of the lecturer. This research was conducted in January-March 2019, with the research subjects being 22 mathematics education lecturers in Banten. While the TPACK questionnaire data analysis was carried out first using Exploratory Factor Analysis, namely Principal Component Analysis (PCA). This analysis tries to find the relationship between a number of variables that are independent of each other so that one or several sets of variables that are fewer than the initial variables can be created. The variables that have the greatest correlation will be clustered to form a set of variables.

RESULTS AND DISCUSSION
The technology used by lecturers in the field of mathematics education in Banten, mostly uses power point applications (40.9%), some others use collaboration between whiteboards, power point applications and interactive computer applications in the teaching process (27.3%). using whiteboard technology as a learning medium (18.2%) followed by collaboration between power point applications and interactive computer applications (9.1%) and using interactive computer applications (4.5%).
For the validity results proven by using factor analysis, it can be seen in Table 2. The main varimax-rotated matrix analysis was carried out to identify whether the items in the scale could be grouped with independent and significant factors. A principal component analysis is concerned with how certain variables will contribute to components as well as with the formation of existing components in the data (Field, 2009). While the lower limit of loading the accepted item factor becomes 0.40 (Field, 2009) This process shows that items TK2, TK, TK5, CK5, PK1, PK3, TPK1, TPK2 and TPACK1 are not related to 7 factors, while other items are related to 7 existing factors. The results of the validity of each item by looking at the results of the correlation value for the items were obtained between r = 0.018 (TK3) to r = 0.929 (TK4). The results of the correlation between TPACK components showed that there was a Thus, PCK, CK and PK are components that have a significant effect on the perception of TPACK in mathematics education lecturers, this result means that mathematics education lecturers are oriented towards pedagogical aspects, content knowledge, while technological aspects have not become a concern, but only become supporting factors such as using in learning media this can be seen from the moderate correlation between TPK and TPACK.  have scores that are above average (good), but there is still a need to make improvements to the lecturers' understanding of the use of the latest technology.
While the analysis of the effect of gender (JK) and length of teaching (LM) on TPACK perceptions using ANOVA at a significance level of 5% and df = 22-1 obtained t table = 1.721, and tcount as in table 4. Mathematics education lecturers' perceptions of TPACK in terms of gender and length of teaching. Thus, it can be concluded that the gender factor has no effect on TPACK perceptions, this is according to several previous studies (Jang & Tsai, 2012;Liang, Chai, Koh, Yang, & Tsai, 2013;Lin et al., 2013). This indicates that they do not understand the use of technology integration within the TPACK framework. The long teaching factor has no effect on TPACK perceptions, as research by Liang, Chai, Koh, Yang, & Tsai (2013) and different from the results of research from Jang & Tsai (2012), this can be due to a lack of understanding of the TPACK framework.
The factors of gender and length of teaching are factors that need to be carried out further studies related to their effect on the perception of TPACK in mathematics education lecturers after socialization of the understanding of TPACK. Research on other factors can also be considered such as technological competence, interaction with technology and learning methods.

CONCLUSION
The results of the research on the understanding of TPACK mathematics education lecturers in Banten found that the TPACK framework of the 7 components was validated, based on the TPACK item, PCK, PK and CK components had a strong positive effect on the perception of TPACK in mathematics education lecturers. This result means that mathematics education lecturers are oriented towards pedagogical aspects and content knowledge, while technological aspects have not become a concern, but only become a supporting factor such as using in learning media. This can be seen from the moderate correlation results between TPK and TPACK. For an in-depth analysis of the gender factor and the length of teaching on the understanding of the TPACK components, it was found that gender and length of teaching had no significant effect between the understanding of mathematics education lecturers on the seven TPACK components.