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Using machine learning to improve student success in education


Deploying machine learning and advanced analytics thoughtfully and to their full potential may support improvements in student access, success, and the overall student experience.

Many education institutions are now using data and analytics as an integral part of their processes. Whether the goal is to identify and better support pain points in the student journey, more efficiently allocate resources, or improve student and faculty experience, institutions are seeing the benefits of data-backed solutions.

Those at the forefront of this trend are focusing on harnessing analytics to increase program personalization and flexibility, as well as to improve retention by identifying students at risk of dropping out and reaching out proactively with tailored interventions. Indeed, data science and machine learning may unlock significant value for universities by ensuring resources are targeted toward the highest-impact opportunities to improve access for more students, as well as student engagement and satisfaction.

For example, Western Governors University in Utah is using predictive modeling to improve retention by identifying at-risk students and developing early-intervention programs. Initial efforts raised the graduation rate for the university’s four-year undergraduate program by five percentage points between 2018 and 2020.

Yet higher education is still in the early stages of data capability building. With universities facing many challenges (such as financial pressures, the demographic cliff, and an uptick in student mental-health issues) and a variety of opportunities (including reaching adult learners and scaling online learning), expanding use of advanced analytics and machine learning may prove beneficial.

Below, we share some of the most promising use cases for advanced analytics in higher education to show how universities are capitalizing on those opportunities to overcome current challenges, both enabling access for many more students and improving the student experience.

The potential of advanced analytics in higher education

Advanced-analytics techniques may help institutions unlock significantly deeper insights into their student populations and identify more nuanced risks than they could achieve through descriptive and diagnostic analytics, which rely on linear, rule-based approaches

Advanced analytics is more sophisticated than other common approaches and could provide a competitive advantage.

Advanced analytics—which uses the power of algorithms such as gradient boosting and random forest—may also help institutions address inadvertent biases in their existing methods of identifying at-risk students and proactively design tailored interventions to mitigate the majority of identified risks.

For instance, institutions using linear, rule-based approaches look at indicators such as low grades and poor attendance to identify students at risk of dropping out; institutions then reach out to these students and launch initiatives to better support them. While such initiatives may be of use, they often are implemented too late and only target a subset of the at-risk population. This approach could be a good makeshift solution for two problems facing student success leaders at universities. First, there are too many variables that could be analyzed to indicate risk of attrition (such as academic, financial, and mental health factors, and sense of belonging on campus). Second, while it’s easy to identify notable variance on any one or two variables, it is challenging to identify nominal variance on multiple variables. Linear, rule-based approaches therefore may fail to identify students who, for instance, may have decent grades and above-average attendance but who have been struggling to submit their assignments on time or have consistently had difficulty paying their bills

Machine learning techniques can surface insights using complex and unstructured data sets.

A machine-learning model could address both of the challenges described above. Such a model looks at ten years of data to identify factors that could help a university make an early determination of a student’s risk of attrition. For example, did the student change payment methods on the university portal? How close to the due date does the student submit assignments? Once the institution has identified students at risk, it can proactively deploy interventions to retain them.

Though many institutions recognize the promise of analytics for personalizing communications with students, increasing retention rates, and improving student experience and engagement, institutions could be using these approaches for the full range of use cases across the student journey—for prospective, current, and former students alike.

For instance, advanced analytics can help institutions identify which high schools, zip codes, and counties they should focus on to reach prospective students who are most likely to be great fits for the institution. Machine learning could also help identify interventions and support that should be made available to different archetypes of enrolled students to help measure and increase student satisfaction. These use cases could then be extended to providing students support with developing their skills beyond graduation, enabling institutions to provide continual learning opportunities and to better engage alumni. As an institution expands its application and coverage of advanced-analytics tools across the student life cycle, the model gets better at identifying patterns, and the institution can take increasingly granular interventions and actions.

Deploying machine learning to harness this potential

Institutions will likely want to adopt a multistep model to harness machine learning to better serve students. For example, for efforts aimed at improving student completion and graduation rates, the following five-step technique could generate immense value:

  1. Analyze 150 or more attributes from multiple years of historical data to understand the characteristics of a “successful student”—that is, someone who graduated within a reasonable time frame.
  2. Define the goal for improving student success for key student segments as compared with a baseline; for example, an institution might aim to improve the graduation rate by 5 percent within a particular time frame.
  3. Build an initial machine-learning model using historical data to identify 30 to 50 attributes that indicate a high risk of attrition, then measure the model’s effectiveness against a baseline, such as the university’s existing measures.
  4. Based on these attributes, build archetypes of students at risk of attrition and backtest for population skews or biases.
  5. Develop and implement tailored interventions best suited for students in each archetype.

Institutions could deploy this model at a regular cadence to identify students who would most benefit from additional support.

Institutions could also create similar models to address other strategic goals or challenges, including lead generation and enrollment. For example, institutions could, as a first step, analyze 100 or more attributes from years of historical data to understand the characteristics of applicants who are most likely to enroll.

Advanced analytics in action: How institutions have improved enrollment, retention, and, ultimately, the student experience

The experiences of two higher education institutions that leaned on advanced analytics to improve enrollment and retention reveal the impact such efforts can have.

A private nonprofit university’s effort to reach more students

One private nonprofit university had recently enrolled its largest freshman class in history and was looking to increase its enrollment again. The institution wanted to both reach more prospective first-year undergraduate students who would be a great fit for the institution and improve conversion in the enrollment journey in a way that was manageable for the enrollment team without significantly increasing investment and resources. The university took three important actions:

  • Allocating ‘top of funnel’ marketing spending to those most likely to apply. The university developed a machine-learning model using advanced analytics to predict which leads (prospective students) were most likely to apply. As a result, the university could identify the top 10 percent of leads, which accounted for about 90 percent of applicants. This enabled the team to immediately pivot its outreach efforts for the subsequent fall to prioritize the top 10 percent of leads yet to apply and ensure a higher return on investment for that outreach. In the future, this gives the institution the flexibility to either decrease its marketing spending to achieve the same number of applicants or maintain levels of spending to create a larger and potentially more competitive applicant pool.
  • Focusing yield efforts on archetypes that predict a high likelihood of matriculation. To complement the advanced-analytics model for predicting which prospective students would apply, the institution developed a similar model for predicting which applicants would enroll. The model incorporated the wealth of additional data generated in the application process and broader demographic data, enabling the university to identify the top 40 percent of applicants, who accounted for about 85 percent of enrollment. Advanced analytics could then segment the high-potential applicants into five archetypes, with varying levels of expected conversion. For example, one archetype was characterized by students who sought out the university (that is, they came from unpaid sources) based on strong interest in particular arts programs, with roughly one in three of these applicants enrolling. This archetype segmentation enables the university to better prioritize and tailor its approach to applicants during the yield period. It also gives the institution future flexibility in targeting enrollment growth versus other strategic enrollment management priorities.
  • Identifying undertapped ‘look alike’ markets: The integration of demographic and other regional data enabled the institution to not only prioritize high-potential future enrollees within the markets where it currently recruits but also identify “look alike” markets. Look-alike markets share predictive characteristics with markets that tend to have a high share of enrolled students, but they are not actively prioritized for recruitment by the college for various reasons, such as one-off past experiences or because they’re less obvious fits. Through list buys that target specific counties, the university increased its reach in look-alike markets, grew its applicant pool by 15 to 20 percent overall, and deprioritized spending in markets with a lower likelihood of conversion.

For this institution, advanced-analytics modeling had immediate implications and impact. The initiative also suggested future opportunities for the university to serve more freshmen with greater marketing efficiency. When initially tested against leads for the subsequent fall (prior to the application deadline), the model accurately predicted 85 percent of candidates who submitted an application, and it predicted the 35 percent of applicants at that point in the cycle who were most likely to enroll, assuming no changes to admissions criteria (Exhibit 3). The enrollment management team is now able to better prioritize its resources and time on high-potential leads and applicants to yield a sizable class. These new capabilities will give the institution the flexibility to make strategic choices; rather than focus primarily on the size of the incoming class, it may ensure the desired class size while prioritizing other objectives, such as class mix, financial-aid allocation, or budget savings.

An online university’s aspiration to enable more student success

Similar to many higher-education institutions during the pandemic, one online university was facing a significant downward trend in student retention. The university explored multiple options and deployed initiatives spearheaded by both academic and administrative departments, including focus groups and nudge campaigns, but the results fell short of expectations.

The institution wanted to set a high bar for student success and achieve marked and sustainable improvements to retention. It turned to an advanced-analytics approach to pursue its bold aspirations.

To build a machine-learning model that would allow the university to identify students at risk of attrition early, it first analyzed ten years of historical data to understand key characteristics that differentiate students who were most likely to continue—and thus graduate—compared with those who unenrolled. After validating that the initial model was multiple times more effective at predicting retention than the baseline, the institution refined the model and applied it to the current student population. This attrition model yielded five at-risk student archetypes, three of which were counterintuitive to conventional wisdom about what typical at-risk student profiles look like

Together, these three counterintuitive archetypes of at-risk students—which would have been omitted using a linear analytics approach—account for about 70 percent of the students most likely to discontinue enrollment. The largest group of at-risk individuals (accounting for about 40 percent of the at-risk students identified) were distinctive academic achievers with an excellent overall track record. This means the model identified at least twice as many students at risk of attrition than models based on linear rules. The model outputs have allowed the university to identify students at risk of attrition more effectively and strategically invest in short- and medium-term initiatives most likely to drive retention improvement.

With the model and data on at-risk student profiles in hand, the online university launched a set of targeted interventions focused on providing tailored support to students in each archetype to increase retention. Actions included scheduling more touchpoints with academic and career advisers, expanding faculty mentorship, and creating alternative pathways for students to satisfy their knowledge gaps.

Advanced-analytics risks to keep in mind

Advanced analytics is a powerful tool that may help higher-education institutions overcome the challenges facing them today, spur growth, and better support students. However, machine learning is complex, with considerable associated risks. While the risks vary based on the institution and the data included in the model, higher-education institutions may wish to take the following steps when using these tools:

  1. Build and train models to ensure they don’t accidentally introduce biases informed by race, age, or gender. Also ensure that new models are not inadvertently building on inherent accidental biases in current methods.
  2. Focus models on use cases that involve supporting and including students as opposed to any decisions that suggest excluding students from certain interventions; the models also should explicitly test factors to remove unconscious bias from any decision making connected to the point above.
  3. Use results and insights from machine-learning models together with, and as input for, existing student support processes. Machine-learning models provide additional insights to inform interventions; they should not be used as a replacement for existing structures and methods.
  4. Consistently check the performance of the model for different student segments to ensure it performs relatively similarly for all segments and is not skewed toward any particular group.

While many higher-education institutions have started down the path to harnessing data and analytics, there is still a long way to go to realizing the full potential of these capabilities in terms of the student experience. The influx of students and institutions that have been engaged in online learning and using technology tools over the past two years means there is significantly more data to work with than ever before; higher-education institutions may want to start using it to serve students better in the years to come.

Extra: Online Coaching For Government Exams in India


Olee Class has launched an online coaching module “Supercoaching” to prepare for various government exams where we have collaborated with some peak institutes all across the country. We have brought in some of the best super teachers under one umbrella, a single platform to prepare aspirants for Government exams. Supercoaching provides online coaching preparation for different exams with profound analysis of subject courses and notes with exhaustive test series and multiple revisions.

Olee class Supercoaching currently covers more than 30+ exams with live sessions, recorded video sessions and many more giveaways. We have bifurcated every course with respect to the syllabus and provided an in-depth explanation for the same at cost effective rates. We have tried to help students with all major exams which are covered under UPSC, SSC, BPSC etc.

For all the aspirants these government exams do hold a lot of value with the increasing competition and few vacancies and to crack these exams it is equally important to study from the right resources and provide correct guidance.

To ensure that the candidates can beat the rising competition we at super coaching provide a platform for our aspirants to help them clear their respective government exams and provide guidance and mentorship with our super teachers, cost effective courses, live and pre recorded video lectures, personalized doubt solving with profound analysis for the subject of their choice.

Every year, there are various exams conducted by the Government of India to recruit candidates for the respective central or state government departments.The reason why government exams are so popular that:

  • Along with serving the nation, it also provides job security.
  • It also has a positive career growth for existing officers to reach higher positions by clearing the inter departmental exams.
  • Authority gained for a post upon clearing the exam.
  • It is a recession proof job.

Supercoaching Preparation for Government Exams

Supercoaching provides online coaching preparation for different government exams, with interactive courses and live sessions and study materials focused on the exam pattern. Helping students study from our own detailed notes, subject matter experts providing one on one mentorship.-

  • Supercoaching is accessible from any device upon successful activation.
  • Live sessions and pre recorded lectures.
  • It saves your time and energy required for traveling as one can study for different government exams from Supercoaching.
  • Personalized doubt solving for every candidate.
  • Pre-recorded lectures for students to study in their own flexible schedule.
  • Easy to understand and user-friendly at cost-effective rates.
  • Well structured notes.
  • Daily updated current affairs.

Prepare for Exams with India’s Super Teachers

We have the best set of Super teachers for online coaching preparation of different government exams through our super coaching program.

Our Super Teachers have made surethat we have covered each and every topic in detail with user friendly notes, in both Hindi and English languages.

These Super Teachers have provided guidance for many candidates and helped them to clear these exams to secure an All India Rank.

We have collaborated with top notch coaching institutes pan India and teachers with years of experience in teaching providing guidance and mentorship to every aspirant to help them clear the exam.

Benefits of Supercoaching

Supercoaching is an online coaching platform for various government exams preparation, we make sure one gets quality education at cost effective rates and guide aspirants to achieve their goals.

  • You need not worry to carry the load of books, we provide study materials that can be accessed from literally anywhere.
  • Supercoaching is for everyone! Be it a working professional, a student or a full time aspirant, we provide a complete package for subject courses inclusive of test series and paper analysis.
  • Daily updated current affairs and in depth analysis of each article on a single platform.
  • Live video sessions for an interactive learning experience.
  • Pre recorded video lectures, so that, in case an aspirant misses out on any, they can compensate for the same by downloading the lectures.
  • Easy to use and flexible, so that a student can study at their own pace and schedule.
  • One to one personalized doubt solving with right guidance for the exam.

How to Enroll in Olee Class Supercoaching?

Lets begin your preparation journey with “Supercoaching”.
Its super easy to enroll for our exams,

  • Log in to testbook.com or testbook app
  • From the home page → click on “Supercoaching”.
  • Select your exam “goal” and choose a plan for your desired course.
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You just need a suitable smartphone or a laptop with a stable internet connection and you can kickstart with your preparation.

Supercoaching Course Fees

The best feature about our Supercoaching module is its fee. We believe these courses at the most affordable rates.

Many offline institutes charge exorbitant fees for aspirants in the name of government exams and coaching without any guarantee that he/she may be able to clear them, to ensure that the candidates can beat the rising competition in government exams, we at super coaching provides one of the best and cost effective courses and almost provide the preparation for government exams for free.

Do check out the course fees for different exams at Testbook App or directly via our site to select the courses of your choice.

You can download the pre-recorded lectures and understand them at your own pace and it is a complete package and there is no need to buy a separate test series, unlike many coaching institutes.

We support UPI payments, Credit and Debit cards, Net Banking with EMI options. * With exciting offers and plans ™

Online Coaching for IAS 2023-2024 Aspirants


Nowadays, online IAS coaching for UPSC Exam preparation is getting popular in the education sector. Through online IAS coaching, students can prepare for IAS Exam anytime anywhere. and If you intend to take the IAS exam, and looking for the best online coaching for IAS in India then In this article, you will all the information about the Top UPSC Online Coaching in India.

Presently, students prefer online IAS classes since it is a convenient method of preparation, especially with students’ busy schedules and even pandemics. However, if you are an IAS aspirant and want to learn more about IAS exam preparation and online tutoring, you should continue reading this post to understand more about the subject. In India, there are various online IAS Coaching that can provide you with the necessary guidance to assist you in acing the exam. As a result, ShikshaCoach assists you in achieving your objectives by connecting you with the best IAS Online classes in India.

About IAS Exam
The Indian Administrative Service (IAS) is one of the 20-odd administrations for which aspirants are enlisted by the UPSC. This test is directed on an all-India premise yearly. It is the most notable test of UPSC. The whole IAS test is conducted in three stages (I) Prelims, which includes two papers of objective types questions (GS and CSAT), and (ii) Mains paper, which includes an aggregate of 9 papers of Descriptive kind questions with two discretionary papers of English and Indian Language. The third stage is the interview, wherein your character and information are inspected for the final choice.
These days, online IAS training for UPSC Exam preparation is in demand in the educational area. This is the most supportive asset for students, workers, and housewives. Online IAS Coaching is a helpful method for preparation from anywhere by India’s top faculties.

Things to consider before joining the best IAS Online Coaching
Online classes are adaptable, cost-effective, and handy, and they come in a variety of modes. Since schools and workplaces have been closed due to the Covid-19 outbreak, online learning websites and online courses have seen a significant increase. Despite the fast evolution of online education since then, it appears to be beneficial to both traditional and non-traditional students. But here’s the deal: in order to select the ideal online IAS coaching, a student needs to consider a number of variables.

Previous achievements: Past performances will give you a good idea of the institute’s reputation, as well as how much extra effort the academy invested to obtain it.
Demo/trial classes: Students are generally given three to four demo/trial courses by a reputable coaching institute. Simply choose the subject and time of the session so that you may acquire an unbiased assessment of the teaching quality.
Fee structure: This is typically the first question raised in Student’s Mind. When you take admission to any coaching centre. Most institutes charge similar fees, but what distinguishes one from the other is the payment choices and discounts available. Many respectable institutes allow you to pay your costs in instalments.
Flexible batch timings: This is a critical concern because students typically begin coaching while still in high school or college, and the coaching centre’s and other private tuition schedules sometimes clash, or students may skip courses due to a variety of personal reasons. A respectable coaching institute will usually reschedule a class but make sure to inquire about whether the class will be held on their timetable or at your convenience.
Faculty: To get a clearer view of which professors are dedicated to a specific subject, it is advised to look at the faculty’s educational qualifications as well as the teacher-student ratio before taking admission to any institute.
Course material: Good coaching must offer Revision tests, tips, and tricks, teaching patterns, interactive classes along with time management tips for building test speed, practicals for GDs, and interviews.

Indian Tutors Online – IB, ICSE, CBSE & IGCSE Online Coaching And Tutoring


Unlock the true academic potential of your child! ICSE/IGSCE/IB/CBSE is considered to be a relatively difficult educational board and includes syllabuses with high-quality parameters. It requires hard work, commitment, and focus on scoring good in an ICSE/IGSCE/IB/CBSE examination. If you are looking for the best Indian tutors for ICSE/IGSCE/IB/CBSE coaching, your search ends here!

At Edugraff, we offer unparalleled online tutoring for ICSE/IGSCE/IB/CBSE curriculum for all grades. Our IB tutors online employ a unique approach to meet your child’s educational needs while saving you a great time and money. We have created CBSE & ICSE online coaching programs based on the key areas of the curriculum. Our unique program is designed and delivered by subject experts with ICSE backgrounds.

Our Uniqueness
Edugraff is a pioneer in providing online tutoring for international boards like ICSE/IGSCE/IB through qualified tutors online. Our tutors work closely with the students and share ideas & experiences to develop their understanding of the subjects. Moreover, they guide them using different audio and video materials to develop higher-order thinking skills and reinforce the concepts in the minds of the students.

Our tutors are experienced with ICSE/IGSCE/IB/CBSE backgrounds and provide activities that improve the critical and analytical thinking of the students. We provide our students with the flexibility to choose their own learning schedule to help them learn at their pace. Our learning programs are created to be fun and interactive to allow children to learn challenging concepts in a relaxing environment. At Edugraff, our goal is that students should get access to quality learning in an affordable way. Having a personal tutor to guide them ensures that there is no distraction, and they learn challenging concepts in a simple way. Looking for the best IGCSE online tutoring in India? Call us now at +91 790 2350 323 to help your child learn better and score more.

Top 10 Best IIT JEE Online Coaching in India with Fees & Contact Details


Due to the current scenario of the pandemic, online coaching classes are the most feasible option for students. Along with this, IIT JEE online Coaching classes are not only more affordable but also time-saving since students can receive knowledge in the comfort of their homes and at any convenient time. They have the advantage of easy access to study materials and video lectures which are also very helpful for revisions.

However, choosing an ideal IIT JEE online coaching centre is not easy since students need to take many features into consideration. Therefore, our team has accumulated a well-researched list of the Best Online Coaching for IIT JEE including their highlighting features and facilities. So scroll down to read them.

About IIT JEE Exam

IIT JEE is the Joint Entrance Examination for Architecture and Engineering Courses administered by the Indian Institute of Technology. Admission to IITs, NITs, and other famous engineering institutes across India is available through this exam. For ambitious engineers, IIT JEE has proven to be a fantastic opportunity. IIT JEE is an exam that is the finest platform for Engineering and Architecture aspirants. The exam allows students to showcase their talent and expertise at the IIT level.


The 3 phases of IIT JEE are – 

  • Mains
  • Advanced
  • Architecture Aptitude Test (AAT).

Top 10 Best IIT JEE Online Coaching Centres

IIT JEE is not a very easy examination to qualify for since it requires a lot of knowledge and hard work. Moreover, more than 12 lakh students attempt this exam every year. But with the right coaching platform, students can crack the examination without much difficulty. This list of the best Online Coaching for IIT JEE is for students to choose their ideal IIT JEE online coaching centre. So scroll down to read them.

Unacademy – Best IIT JEE Online Coaching

Unacademy is a top IIT JEE online coaching platform that was founded by Mr Gaurav Munjal in 2015. It is an online learning platform that allows users to watch online videos generated by expert educators of their curriculum. The educators coach students for most of the popular competitive exams like Boards, IIT JEE Mains and Advanced, NEET, GATE, UPSC, CAT, etc. Unacademy is India’s foremost learning platform with headquarters in Bengaluru.

The faculty consists of expert trainers from across the country. They strive to provide the best quality training to thousands of aspiring students which makes them one of the most sought-after faculty teams. Unacademy provides two subscription models – Plus and Iconic. Additionally, students receive well-structured notes, one-on-one online Live Mentorship, and Live Doubt Solving Sessions with specialists as part of the Iconic Subscription.

Why should you join Unacademy?

  • Free online demo classes.
  • They conduct Daily live classes and practice questions.
  • Unlimited access to all the live and recorded courses.
  • Test series and live test quizzes.
  • You will get Training in English, Hindi, Malayalam, Tamil, and 12 other languages.
  • They also conduct Live Doubt Clear sessions.