Telebort is a company with a mission to enable kids and teens from eight years old until pre-university to solve real world problems through coding. Hence, Telebort offers a full spectrum of Computer Science education such as learning material, question banks, real world projects for kids and teens to learn Computer Science. We believe that what kids learn today shapes the world we live in tomorrow. We aim to give every child the skills, confidence, and opportunity to express themselves in the digital world.

As a company with a mindset to always strive to thrive, we always try our best to improve in every way in order to maximize our success and to cope with the competition. Hence, we set up a team of five to analyze the weekly feedback form and to further improve its functionality. This is important because we can further analyze the students’ learning experience with Telebort through the analysis. We as an institute that prepare the youth for the future really need to take one step above to make students enjoy and fully prepared for learning. The main aim is to make sure our students are having maximum satisfaction during their class with Telebort.

In the first part of this article, we will start with a **brief introduction to our data** before we dive into the analysis about these data.

The five aspects to enhance classroom experience we found are **Lesson_new**, **Lesson_enjoy**, **Like_programming**, **Lesson_understanding** and **Teacher_preparation**. The explanation of each aspect will be covered in the next section.

Next, we will show the result of our analysis about why the 5 aspects are important in improving the classroom learning experience. We will be showing:

**Correlation coefficient results****Linear Regression coefficient results**

All the analysis is done by using Python with Google Colaboratory and related data analysis libraries (Pandas, Scikit-Learn, etc.)

Lastly, we share our experience in **how to use these aspects to enhance the classroom learning experience** by some simple examples.

Our dataset consists of the respondents from all the students that had submitted their feedback through Telebort’s weekly feedback form. **Figure 1.1** shows the sample of our dataset. Some facts about the weekly feedback form:

- The main purpose of collecting the feedback form is to analyze the satisfaction of our students when learning with Telebort.
- The responses are collected from the year 2016 to year 2021.
- The forms have different versions since we have different kinds of programs, such as Fast Track Program, Holiday Program and Core Program. Each version will have some different questions that are suitable to each program.
- The total amount of data collected by the start of the analysis is 6747.

From the weekly feedback form questions, we specify the **satisfaction of students in class** as the main factor. Meanwhile, we took the questions that we ask the students in the feedback form as the independent variables to analyze the factors that affect students’ satisfaction. All the variables are rated from 1 to 5 as below:

Dependent Variable (Y):

**Satisfaction of students in class**

Independent Variable (X₁):

**Lesson_new**: How much they have learned something new during the class.

Independent Variable (X₂):

**Lesson_enjoy**: How much they enjoyed the class for that day.

Independent Variable (X₃):

**Like_programming**: How much they like programming.

Independent Variable (X₄):

**Lesson_understanding**: How much they understand the lesson they learned during the class.

Independent Variable (X₅):

**Teacher_preparation**: How far they thought of the teacher’s preparation for the class.

Correlation coefficient are used to measure the strength of linear relationship between two variables. The formula is as follows:

The range of values for the correlation coefficient(r) is 1.0 to -1.0 where

- r > 0: Positive correlation
- r = 0: No correlation
- r < 0: Negative correlation

Figure 1.3 below shows the variables that are used for the correlation.

Based on Figure 1.3, there are some key results:

- Lesson_new, Lesson_understanding and Teacher_preparation have a positive correlation (r > 0.4) with the satisfaction of the students. These aspects significantly affect the satisfaction of the students compared to the other aspects.
- Lesson_enjoy and Like-programming have low correlation coefficient (<0.4) with Y which means these aspects give a slight impact to the satisfaction of students.

Linear Regression analysis is used to quantify the relationship between two or more variables. The goal of performing regression analysis is to generate the equation that explains the relationship between independent and dependent variables.

Before running the regression analysis, we must make sure that our data is fitted and able to continue with the analysis. First, we plot the residual plot for the Ridge Model. We plot the ridge model with histogram and Q-Q plot to determine if the data set is well-modeled by a normal distribution. Figure below is the result:

Then, we can get the regression coefficient of each aspect towards the Y. The higher the regression coefficient, the greater impact the aspect can give to Y.

The formula of linear equation with regression coefficient,m and regression Interception,c as follows:

Y = 0.338567X₁ + 0.334638X₂ + 0.159652X₃ + 0.135931X₄ + 0.112686X₅ - 1.807548

where the increment of a unit in each aspect X₁ , X₂ ,X₃ ,X₄ ,X₅ will contribute to satisfaction learning to students according to their regression coefficient respectively.

**Remarks:** Other aspects in the feedback are not covered as their regression coefficients are not significant (<0.1).

Let's take note of the highest contribution of that criteria, Lesson_new. One unit increment on Lesson_new will contribute about 0.339 satisfaction to the students' learning.

Hence, we know that

- Lesson_new and Lesson_enjoy shows the significant impact on the students’ satisfaction as having the higher value (>0.3) for regression coefficient.
- Like_Programming, Lesson_understanding, and Teacher_preparation still have a great impact on the students’ satisfaction as having the positive value (>0.1) for regression coefficients.

The higher the coefficient of determination R², the higher percentage of points should fall within the regression line. From Figure 1.5, the R² is around 0.55 which implies the data has a good fit for the regression model.

When students are having a great time learning in class, they will be able to grab everything they learn without much difficulty. As an instructor or teacher, it is our responsibility to make sure that the class we are conducting is in the best condition. So here we have listed 5 aspects that can enhance the classroom experience.

From our analysis, we can conclude that the most important factor that leads to students' satisfaction in class is when they are able to learn new things. Students will always be interested to learn something new. Here in Telebort, when we plan our program syllabus, we will make sure the students learn something new in each lesson. For example, in the previous class we taught about text components in HTML, then in the coming class the students will learn about how to insert images and videos in HTML. This will spark the students’ curiosity and increase their interest to learn more and stay focused.

Secondly, we can see that enjoying the lesson is one of the factors that can affect a student's satisfaction. Fret not, in Telebort, we will provide interactive notes, videos, and prepare various activities in each lesson to make sure the students enjoy their learning. When we make notes for the lesson, we make sure to add a few related photos to the lesson so that the students are able to visualize the concept they learnt. We also explain in detail about the programming concept they learnt in the lesson videos. As for lesson activity, we prepared fun and interesting activities to make students think that programming is not that hard and they can enjoy the learning process. We always try to make learning with Telebort a fun learning experience every time.

From our analysis, the third factor that impacts the satisfaction of students in class is their love towards programming. Of course if they are interested in the things they learn, they will focus more. Learning can only happen when someone is interested. They will push to their limits and explore things by themselves. We can imply this finding that when a student is learning something they love, they will be at their best in class and ready to learn. Hence, we need to increase the students' interest and eagerness to learn. For example, Telebort’s academic team provided a lot of resources like videos, articles and websites to show to the students. This makes the students understand that learning is not only through textbooks but everything around us because learning programming is not something we can simply learn from just textbooks. We try to implement the ability to solve real world problems using coding to our students such that we can easily search and grab the thing we want both online and offline.

Besides that, the students’ understanding is having a great impact on students’ satisfaction in class. The teacher or instructor that is responsible for the class needs to make sure that every student understands the lesson they learnt. Students do not learn much just sitting in classes listening to instructors, memorizing assignments, and spitting out answers. In Telebort, the teachers are well trained to teach and at the same time have great interactions with students. Education is a two way process. From the interaction between the teacher and student, we can easily know the progress of the students whether they can understand the lesson, paying attention in class and more. Students are also always encouraged to ask questions from time to time in the class.

Also one of the important factors that affect student’s satisfaction that we are able to identify from our analysis is the teacher's preparation. Teacher is the driver for the learning journey. If the teacher is well prepared, he/she can teach and explain well in the class. Teachers in Telebort possess the skills and knowledge necessary for effective teaching, as well as sufficient knowledge of the subject matter to be taught. What we do in Telebort, teachers or instructors will need to undergo intensive training on the program to be taught. It is a must for a teacher to go through every material and do the projects. At the same time, mock teaching must be given to new teachers to make sure they can explain the content well enough.

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