Gathering And Analyzing Data About Students in A Classroom

 

Gathering And Analyzing Data About Students in A Classroom

Author: Santosh Kumar Biswa, Sr. Teacher, Damphu CS, Tsirang, Bhutan

                                                                                            

Regardless of the differences and impairments of the pupils, teachers should always strive to improve learning in the classroom. By learning more about how students learn and use that knowledge in an inclusive classroom to design and implement education that is specific to each student's needs, the achievement gap in the classroom can be closed. To effectively close the learning gaps, teachers must make sure that correct data is acquired regarding the range of sources from which pupils learn (Lawrence, 2016). They are free to use whatever technique to get information from their students. If one approach is unsuccessful, one must choose an alternative so that the right information can be obtained. The following are two techniques I might employ to compile and examine information about pupils in a classroom:

1.     Assessing student’s performance continuously in the classroom: I assess my students' performance by continuously conducting assessments and evaluating their performance by collecting data on how the students are performing, how well the materials are used or accepted by the students, and whether they are motivated by the teaching style in the classroom (Resilient Educator, 2022). Assessment can be accomplished through a variety of activities such as short quizzes, writing assignments, question-and-answer drills, observation of student behavior, summative data through unit tests, a fun project for information, ad-hoc tests, and so on. This will enable me to decide which direction to take the class further after analyzing the data because I will be observing their behavior, performance, learning outcomes, the effectiveness of the teaching materials based on the report presented by them, etc. to know exactly what is lacking or hampering their learning progress based on the observations made. I will be able to obtain clear knowledge from my students to meet educational objectives. Some data will be captured without the student’s awareness so that I can look for ways to engage the student’s interest so they can generate their information (Resilient Educator, 2022). According to Lawrence (2016), if we align relevant content and performance standards to the actual content taught in classrooms, learning will proceed successfully.

2.     Learner Analytics: This is what I mostly do in my classroom and is the most successful process of collecting and analyzing data. It can be used across all the levels of an inclusive classroom ranging from K to 12 to benefit students. In my school, all teachers are asked to collect data based on the student’s academic performance, after which we are asked to analyze the data collected. We analyze the data following Bloom's taxonomy pattern, after which we come up with the strategic plan for the next term. As a result, we have a precise understanding of our students' performance, where they require remediation, and what they require in terms of support. It allows us to obtain precise information about our students and the areas of Bloom's taxonomy in which they require assistance. We can track their performance, especially those students who are weak. Simultaneously, by customizing the lesson, we can design appropriate activities and monitor their level of engagement. On the other hand, we also collect the backstories of our students to analyze, evaluate, and scrutinize details about how our students learn, what their interests are, what hinders them from learning, and what their interests are. Based on the data collected, we plan our instructional practice through a process called "data-driven decision-making" to suit the needs of our learners (Lawrence, 2016). It enables teachers to have knowledge about their students and to come up with the right learning activities for diverse students.

How learner analytics is meaningful to diverse students in the inclusive K-12 classroom

Learning analytics about student knowledge is used for more than just automated adaptation that helps teachers assess and support learning and performance to enhance engagement and affect (Baker, 2016). According to Dani (2019), "learner analytics" refers to data gathered based on students' academic performance and the analysis of their learning trends that reveal areas for improvement. It can be used in a K-12 inclusive classroom because it involves teachers in researching how their students are progressing based on data collected and customizing their teaching and learning processes based on their understanding of the necessary supports they can provide to make learning effective for each student. The main purpose of learning analytics is to find out potential problem areas for each student and take timely action to address them (Norwood, n.d.). Learner analytics is meaningful to diverse students in the inclusive K-12 classroom because teachers are involved in tracking those students who are academically weak in a continuous manner and have detailed insight into the performance of each student. Moreover, they will also be engaged in tracking the participation and engagement level of each student in the classroom based on the analytics report collected. On the other hand, knowing that every student has a different learning style and ability, teachers customize their lesson plans based on the learning pattern presented in the analytics report. They can even involve themselves in redesigning the lesson based on the learning pattern presented in the analytics report. The advantages of learner analytics are that teachers can easily identify those students who are at risk and improve the overall quality of teaching by providing personalized learning in the classroom. Most importantly, the data collected through learner analytics can assist teachers in making decisions to ensure that resources are placed where they are needed most so that students can cement their understanding through collaborative learning and have access to one-to-one learning (Nielsen, 2019).

Data is more readily available to teachers than ever before, providing them with critical information about how their K-12 students are progressing through the learning process. 

References

Baker, R. (2016). Using learning analytics in personalized learning. In M. Murphy, S. Redding, & J. Twyman (Eds.), Handbook on personalized learning for states, districts, and schools (pp. 165–174). Temple University, Center on Innovations in Learning. https://learninganalytics.upenn.edu/ryanbaker/ED568173.pdf

Dani, V. (2019). 5 Ways to Use Learning Analytics in K-12 Classrooms. https://kitaboo.com/use-learning-analytics-k-12-education/

Lawrence, K.S. (2016). Identifying data-driven instructional systems. Research to Practice Brief. SWIFT Center. https://files.eric.ed.gov/fulltext/ED571845.pdf

Nielsen, T. (2019). Why learning analytics benefits instructors and learners? https://www.totaralearning.com/en/blog/why-learning-analytics-benefits-instructors-and-learners

Norwood, A. (n.d.). Why is Learning Analytics Important to the Learning Journey? https://schoolbox.com.au/blog/why-is-learning-analytics-important-to-the-learning-journey/#:~:text=Through%20understanding%20data%2C%20your%20teachers,tailor%20their%20pedagogy%20to%20suit.

Resilient Educator. (2022). Collecting Data in the Classroom: A Teacher's Guide. https://resilienteducator.com/classroom-resources/collecting-data-in-the-classroom-a-teachers-guide/