Recently in a survey done in the United States, a teacher at a secondary school stated that if he had data before his students entered the class, it would help him to know how exactly he should start with each one of them and how the lesson plans must be made. “It would be incredible”, he added.
This might come across as a very simple demand which can be fulfilled easily but it would require a lot of brainstorming. In order to provide the teachers with students’ insights which can be acted upon individually and collectively would require a system which is capable of managing multiple sources of data. If the focus is not only to supply insights but also to give valuable inputs in terms of recommending actions, then it becomes important to help them in managing the multiple options of interventions and digital content.
Addressing the issue of Data Privacy
It has been observed in the past that teachers, guardians as well as students are always up for methodologies which can lend personalized instruction and learning for each student. However, there is the genuine concern of data privacy and access protections of a student. This is a real and acceptable issue which can influence the policies or regulatory frameworks and hinder the data sharing which is required to enable personalization. Making sure that the issue of data privacy is tackled properly is imperative for this plan to work and achieve goals.
When it comes to education, the data privacy is as sensitive an issue as it is in the case of healthcare. Majority of developed nations have an established personal electronic healthcare record which is supplied to the healthcare providers. Recently in a published education paper from IBM, there is a quote from “2020 Vison: AHistory of the Future,” which says that – “If fifty percent of the patients who come to a hospital die then the hospital is closed. Similarly, in education if fifty percent students drop out.. Another class is brought in.”
Having said this, we should understand that this healthcare data creates two different scenarios which should be considered. One is the case where there is a one to one doctor-patient interaction where the data can be categorized as highly sensitive. The other scenario is where the doctor does his research from all the available data to decide the next step wh
ich renders the data anonymous.
Let us observe a cognitive approach to lend a personalized touch. Similar to the case in healthcare, the data collected about a student i.e. the personal records follow him through his entire education path. Advanced intelligent assistants can use anonymous data in order to keep a teacher informed about a particular student and supply personal recommendations.
Let us understand this with a small example. Here is a hypothetical conversation between a teacher and a student which explains the idea of cognitive intelligent assistants in the best manner –
Teacher: Rahul, you did fairly well in your Maths exam, scoring 75 percent. Although, it looks like that you face difficulty in questions from trigonometry. Is this assessment correct?
Rahul: Yes, I have a hard time understanding the concepts of trigonometry. Are there any specific areas where I can improve?
Teacher: Well, let’s refer to my cognitive assistant.
Cognitive-enabled teacher assistant: Analysing Rahul’s learning patterns and his performance in the last three examinations; trigonometry comes out as a relatively weak area for him in mathematics. Deriving from the learning outcomes of half a million similar standard 10 students with matching characteristics, it is suggested that a review of module 4.1 and instructional video 5 can help him improve.
Teacher: Rahul, in my opinion you should watch this instructional video which suits your learning style. I suggest you start doing this and then we would observe your performance in trigonometry during the next exam.
This example is a clear indicator of how understanding both the assessment data of the student, his examination marks and knowing a particular student offers a cognitive system which helps the teacher as well as the student.
Until recently, computing was limited to programming done through human-defined inputs. On the other hand, cognitive systems learn with experience. These systems communicate with humans in a natural manner to interpret data, learning with every interaction and proposing new possibilities through reasoning, which strengthens the ability of human decision making. The above example shows that not only is data being collected through various sources of information about the student, but it also analyzes the data gathered from other students and its outcomes. This combination of information and experiential sources and interactions enables to come up with apt recommendation for a specific situation.
All of this is not possible without the power of big data analytics. So much data which would be gathered during these cognitive intelligence projects needs to be analyzed in the most accurate manner to deliver best results. This shows how quickly the idea of Big Data is seeping into one of the most integral parts of our lives – Education. Big data has proven to be helpful to all the areas it has set its foot in and it is ready to bring about a tremendous change in the way we teach and educate the younger generation. With all this information available, it goes without saying that, Big Data has a lot to offer not only in terms of services but also in terms of employment.
A Big Data professional gets to work in so many challenging areas and makes big bucks while doing this. If you are fascinated with analytics and wish to make a career in Big Data, then enrol in Collabera’s Big Data training program today and give your career an unprecedented growth. For more information, you can write to us at firstname.lastname@example.org or visit us at www.collaberatact.com