Development of thought leadership work
Explore different types of learning (online offline) and technologies been applied when needed utilizing a number of sources and advanced secondary research techniques (desk research, interviews of SMEs, surveys).
Conduct in-depth research on geographic and/or horizontal segment trends, competitors, industry market trends and issues, and relevant technology.
Our expertise has an understanding of quantitative and qualitative research skills, with the ability to synthesize findings from case studies, analysis of survey data, regression analysis, expert interviews etc.
• Our analyst team write reports, points of views, articles in journals, blogs, develop insightful case studies, design questionnaire, analyse data, run regressions and time series analysis.
Individual Learners data for Policy levers and context are shaping educational outcomes.
• Collect data through social media network including FB, Blogs, YouTube, Twitter and other similar tools to identify individual attitudes, engagement and behaviour.
• Data Specific to Learner’s Emotion data (boredom, Confusion, frustration, and happiness)
To evaluate the quality of instructional delivery, Pedagogy and learning practices and classroom climate.
To evaluate the quality of instructional delivery, Pedagogy and learning practices and classroom climate.
• Competitors
• Technologies
• Student demographics (Input data) – attendance, enrolment, grade level, ethnicity, gender, first language, health issues, SE status
• Student achievement – questioning in class, criterion-reference test, grades, teachers observations, tests, quizzes, grade point average
• Teaching and assessment practices – instructional and learning strategies, instructional time and environment, assessment practices, classroom management philosophies
• Parent Opinion and behaviours (e.g. perceptions, involvement and support)
• School Culture (e.g. the relationship between educators, students, beliefs about learning)
• Staff demographics (e.g. interest, gender, ethnicity)
• Program (e.g. description, course outline)
• Resource and materials
Physical plant
Improve student satisfaction and retain at-risk students.
How can we maximize student retention?
External alumni involvement and realize donor contributions
How effective are we in engaging alumni in the long run?
Exploring student-teacher interaction
Identify the relationship between learners’ behavioural pattern and diagnosing student difficulties?
Behaviour profiling to profile anomalous behaviour of the students
Student-teacher interaction analytics
Reach and capture the most desirable prospective students.
How can I efficiently and effectively reach out to them and optimize acceptance of enrollment
Increase application volume and achieve enrollment targets.
What is the journey of recruiters through the hiring process?
Faculty’s skills that predict the learner’s performance. How effective is the teacher from the perception of students? What resources are being used by teachers / instructors?
In this section, we provide regional comparisons between educational systems and offer analytics on performance, profiles, observable and administrative differences, as well as benchmarking institutions within the system. Our goal is to provide valuable insights to improve academic excellence.
Utilizing advanced techniques, we classify and cluster student behaviors to gain deeper insights. Our system can automatically detect affective states like confusion, frustration, and boredom. Additionally, we group students based on their personal characteristics, enabling effective behavior profiling to identify anomalies.
Exploring school culture is another key aspect of our analytics, where we delve into the relationships, beliefs, and attitudes within the educational institution. Staff demographics, such as interests, gender, and ethnicity, are also considered in our analysis.
Additionally, we provide detailed program information, including course descriptions and outlines, and assess the availability and utilization of resources and materials. Finally, we evaluate the physical environment of the school, ensuring that facilities are conducive to effective learning.
We gather data from Learning Management Systems to assess instructional quality, pedagogy, learning practices, and classroom climate. This includes information from platforms like Moodle or Desire2Learn, tracking factors such as resource usage, posting frequency, and login patterns. Our analysis informs effective decision-making.
Our services extend to tracking stakeholders to evaluate education and learning outputs and outcomes. We identify antecedents and constraints, monitor the learning and working conditions of students and teachers, and provide effective data analysis for informed decision-making.
To boost application volume and meet enrollment targets, we assess the student’s journey through the enrollment process. We identify opportunities for enhancing the student experience and improving recruitment processes, ensuring a smoother journey for both students and recruiters.
For efficient recruitment, we segment prospective students and model churn factors. We aim to reach and capture the most desirable applicants while understanding their decision-making processes. Our goal is to optimize enrollment acceptance.
Our data encompasses a wide array of student demographics, including attendance records, enrollment statistics, grade levels, ethnicity, gender, language preferences, health information, and special education status. We analyze student achievement by scrutinizing in-class interactions, test scores, grades, and teacher observations.
Furthermore, our evaluation extends to teaching and assessment practices, covering instructional strategies, classroom environments, assessment methods, and management philosophies. We examine parent opinions, looking into their perceptions, levels of involvement, and the support they offer.
Today, industries are now adopting the Internet of Things (IoT) based wearable technology, and these technologies pose grave privacy and security risk about the data transfer and the logging of data transactions. In healthcare, security and privacy threat are endangering the patient’s life.
At Statswork, we applied hybrid advanced cryptographic primitives, including DES, TDES, AES, E-DES, BLOWFISH pallier, RSA, ELGamal. The performance of the existing hybrid algorithm was compared with the standard algorithm to ensure its accuracy.
Communication Technology
With the incredible growth of mobile data generated on the Internet of things, and the explosion of wireless applications, such as the fifth generation (5G) technology, augmented reality (AR), virtual reality (VR) which all make future wireless communication system more demanding. AI is influencing wireless communication and help overcome radiofrequency RF complexities. At Statswork, we offer AI algorithms like ML and DL which can invoke data analysis to train radio signal types.
Our experts not only develop algorithms but also analyse its performance in comparison to standard algorithms through various metrics such as sensitivity, specificity, by plotting a receiver operating characteristics.
