JOSHanndo

AI is levelling the playing field, empowering startups and large enterprises to innovate rapidly by democratizing advanced technology and specialized skills.

How AI brings corporate might to small teams AI is levelling the playing field, empowering startups and large enterprises to innovate rapidly by democratizing advanced technology and specialized skills.

Coming soon, watch out

What is the future of global education?

The future of global education is poised to undergo significant transformations driven by technological advancements, shifting societal needs, and evolving educational philosophies. As we look forward, several key trends and developments are likely to shape the landscape of global education.....watch this space

What is SPSS? Definition, Features, Types and others

15 July, 2024

Data analysis is one of the most flourishing fields right now as businesses around the world are trying to make sense of their data. However, there are a number of data analysis tools available in the market. In this article, we are going to discuss the Statistical Package for the Social Sciences (SPSS): one of the most-used statistical analysis tools.

In this article, we’re going to explore:

What is SPSS software?
What are the core features of SPSS?
Types of SPSS
SPSS by industry: Use cases
Benefits of SPSS predictive analytics (for all industries)
Advantages of SPSS
Limitations of SPSS
What is SPSS Software?
It is a suite of software programs that analyzes scientific data related to the social sciences. SPSS offers a fast-visual modeling environment that ranges from the smallest to the most complex models. The data obtained from SPSS is used for surveys, data mining, market research, etc.

SPSS was originally launched in 1968 by SPSS Inc., and IBM acquired it in 2009.

SPSS is popular because of its simplicity, easy-to-follow command language, and well-documented user manual. Government entities, educational institutions, survey companies, market researchers, marketing organizations, health researchers, data miners, and many others use it for analyzing survey data.

What are the Core Features of SPSS?
The core functionalities offered in SPSS are:

Statistical program for quantitative data analysis – It includes frequencies, cross-tabulation, and bivariate statistics.
Modeler program that allows for predictive modeling. It enables researchers to build and validate predictive models using advanced statistical procedures.
Text analysis helps you derive insights from qualitative inputs through open-ended questionnaires.
Visualization Designer allows researchers to use their data for a variety of visual representations.
Apart from the above four functionalities, SPSS also provides data management solutions. Its data management solutions like FHIR enable researchers to perform case selection, create derived data, and perform file reshaping.

SPSS predictive analytics

SPSS features that make it a must-have analysis tool:
SPSS is a popular tool for research, experimentation, and decision-making. It is one of the most widely used statistical software worldwide in the world for its attractive features. Here are some of them:

Using SPSS features, users can extract every piece of information from files for the ex*****on of descriptive, inferential, and multiple variant statistical procedures.
Thanks to SPSS’ Data Mining Manager, its users can conduct smart searches, extract hidden information with the help of decision trees, design neural networks of artificial intelligence, and market segmentation.
SPSS software can be used to solve algebraic, arithmetic, and trigonometric operations.
SPSS’s Report Generator feature lets you prepare attractive reports of investigations. It incorporates text, tables, graphs, and statistical results of the report in the same file.
SPSS offers data documentation too. It enables researchers to store a metadata directory. Moreover, it acts as a centralized information repository in relation to the data – such as relationships with other data, its meaning, origin, format, and usage.
Statistical methods that can be leveraged in SPSS:
Descriptive Statistics – It includes methodologies such as cross-tabulation, frequencies, and descriptive ratio statistics.
Bivariate Statistics – It includes methodologies such as means, nonparametric tests, correlation, and Analysis of Variance (ANOVA)
Predicting numeral outcomes such as linear regression
Methodologies such as cluster analysis and factor analysis which is great for predicting for identifying groups.

Rudiments of Research

Basically, to know what research is we need to understand the word ‘research’. ‘Re’ is a prefix, from dictionary.com, it is stated that it is a word loaned from Latin meaning again that is repetition. So we are done with ‘Re’ let’s move on to ‘Search’, from Merriam-Webster, it means to look into/over carefully or thoroughly in an effort to find or discover something.
We now know the structural meaning of research which means finding something again or going over a previous work again.
According to Clarke and Clarke, “Research is a careful, systematic and objective investigation conducted to obtain valid facts, draw conclusions and established principles regarding an identifiable problem in some field of knowledge”.
In starting a research the topic chosen must not be totally new, it could be to continue from were a previous research stopped, to address gaps in another research, to validate a previous research or to counter a previous finding. After choosing your topic, what next?

The Rudiments
Lest I forget to tell you a research can be quantitative or qualitative. Quantitative deals with numbers using surveys (of any kind), polls or other form of data collection that give results in numbers and these numbers are used to draw inferences while qualitative deals with non-numeric data by using interviews, discussions and observations to draw inferences (these modes of data collection do not support large sample size). So before you start, you will need to decide what kind of method will be used to gather data.
Let’s start,
Choose a Topic
In choosing a topic, you will have to go with what interests you. Do not go too hard on yourself trying to please the world. Your topic can be an answer to a problem or a finding into what caused the problem.
Seek Experienced and Professional Guidance
If you are a student, talk to your assigned supervisor to know his/her stance on the topic and advice on how to go about it. Remember they have done it before (maybe a handful of times too).
Source for Materials
This is where a lot of people find difficult. Source for materials relating to your topic like a hungry lion on rampage. Journals, books, library catalogue and other documents will be of great help. The internet will be of great help if you use it right by searching for key words in your topic.
Statement of Problem
This explains the problem to be solved, how it would be solved and why it should be solved. It should be clear and brief.
The Work Begins
A good outline is a great requisite for any research paper. Your points must flow smoothly and review previous work done that are related to your topic to get insight. Your research outline should look like this;
Title page
Abstract (This is a summary of your work)
Introduction (In here you introduce your topic, give the statement of problem, gap of research, research objectives and questions)
Literature review (it may contain a conceptual review, theoretical review and empirical review)
Methodology (steps on how and what will be used to solve the problem )
Findings/ result
Discussion
Conclusion
References
Appendix (if any).
Done?
Do not be tired, you did it. Here comes the dotting of i’s and crossing of t’s. Cross checking for sequence, punctuation, spelling, appropriate use of referencing method, etc. A second eye would be needed to ascertain your work is error free.
Use the recommended referencing format for your institution or the journal were your work will be published in.
Voila! Good luck!

P.S. Do not despair when things are not going right or according to plan, keep an open mind and talk to an experienced person.

Dictionary.com | Meanings & Definitions of English Words The world's leading online dictionary: English definitions, synonyms, word origins, example sentences, word games, and more. A trusted authority for 25+ years!

Let's be your plug in this school season for school shoes

You may contact us for your footwears

ARTIFICIAL INTELLIGENCE
AI In Education: 5 Practical Applications
Here's a hand-picked list of top applications of AI in education. From learning assistance to administrative task automation, learn how AI is shaping the edtech landscape.

Artificial Intelligence in Education: Overview
Learning assistance and better classroom experience
Personalization and closing knowledge gaps
Improved accessibility
Outside-the-classroom tutoring
Improved testing, grading, and assessment
Automation of administrative tasks
Final thoughts
For the last few decades, AI has been transforming ways in which we work and learn. Today, AI has even reached the ability to teach humans.

While artificial intelligence isn't here to replace teachers, AI-assisted learning methodologies have already impacted education. These models benefit teachers and students by automating mundane tasks, providing a personalized learning experience, and more.

In this article, we’ll cover the following applications and benefits of artificial intelligence in education:

Learning assistance
Personalized education
Improved accessibility
AI tutoring
Automated and improved grading
Accurate AI file analysis at any scale
Turn images, PDFs, or free-form text into structured insights

Try for free
If you’re looking to build AI solutions for your own educational use case, check out:

V7 Image Annotation
V7 Video Annotation
V7 Model Training
V7 Dataset Management
Or get in touch with our team to discuss your project!

And now, let’s dive in.

Artificial Intelligence in Education: Overview
As the adoption of AI in education is growing at an exponential rate, so does the interest from market leaders.

The market size for AI in education was valued at US$ 1.1 Billion in 2020. According to UNESCO reports, it’s expected to grow to around US$ 6 Billion by 2024—a substantial growth of 445% in only four years. Market Research Engine report expects the market size to reach US$12 Billion by 2027, another projected increase of 100% in three years.

ai in education market
Source: psmarketresearch
AI is also crucial to UNESCO’s efforts to fulfill Goal 4 of 17 Sustainable Development Goals by 2030—“ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.” With this, the UN aims to fulfill the promise of "AI for all" in hopes that technology can help offer equal learning opportunities.

Combining technology with conventional teaching methods has several benefits. They range from intelligent tutoring systems and smart content creation for students to automating administrative tasks. Let's go through a few common applications of machine learning in education.

Learning assistance and better classroom experience
Artificial intelligence tools can help students understand complex subjects and present simple yet intuitive explanations for an enhanced learning experience.

A prime example of such a tool is the Microsoft Math application. This Optical Character Recognition (OCR) based application recognizes mathematical equations from images and returns the solution. It also presents a detailed step-by-step solution, including explanations and interactive graphs to allow students to learn better.

Source: AI Lab Microsoft Math
While Microsoft's application focuses on just mathematics, some other AI products provide a well-rounded experience for student learning. For instance, virtual assistants created by Cognii use advanced Natural Language Processing (NLP) techniques to converse with students via chatbots. Being one step ahead of normal conversational AI, these AI-powered chatbots ask subject-related questions and provide feedback on the answers received.

AI can also enhance the classroom experience to improve the quality of education and engage students. For example, Blippar’s computer vision-based technology brings immersive visual learning. Their augmented reality builder playground allows educational institutes to bring textbook material to life. This means students can experience visual spectacles like the solar system or a volcanic eruption in a 3-dimensional virtual space.

AI tools can also assist teachers in better understanding their students and improving the efficiency of classroom-related tasks. Microsoft Teams for Education offers Education Insights that use data analytics to inform educators of students’ engagement, learning progress, and well-being. It also includes a vast library of digital apps, such as Reading Progress, that inform instructors of the student's progress and potential areas of improvement.

💡 Pro tip: Check out V7’s Optical Character Recognition tool
Personalization and closing knowledge gaps
Every student has different strengths, weaknesses, and learning styles. Artificial intelligence software can learn from students' study patterns and deliver personalized learning paths, aiding teachers who cannot divide their attention among all students at once.

Companies like Content Technologies and Carnegie Learning have developed smart platforms that use AI to provide personalized learning and feedback to students from pre-K to college. Their intelligent instruction design can identify knowledge gaps, redirect to new topics and create learning content catering to individual needs. As Content Technologies claim,

"Our AI systems can create with a staff of 20 what it would take a large publisher with a thousand employees to replicate. We are breaking down the cost barriers and have proven that AI can produce better content in less time at a fraction of the cost".
V7 Go interface
Solve any task with GenAI
Automate repetitive tasks and complex processes with AI

Try for free
Improved accessibility
Some students require special attention and distinctive learning methodologies, which might make them feel isolated in a traditional classroom setting. Artificial intelligence can boost accessibility for students with hearing or visual impairments, physical disabilities, or those who don’t speak the language well.

Tools like audio transcribers, included with MS Teams, can help students with hearing impairments understand lectures. Speech-to-text technology can also help in taking class notes or performing written exams. For example, Speech recognition software by Nuance claims to have a transcription speed of 160 words per minute and is beneficial for students with limited writing capabilities.

These tools bring new meaning to on-site and online education, ensuring every student has an equal opportunity to perform academically.

Outside-the-classroom tutoring
Artificial Intelligence chatbots prove to be helpful for students that require additional tutoring after school. The goal is to enable students to converse with the bots as they would with real teachers, providing a personalized, one-on-one learning experience.

School closures during the pandemic entrenched the need for AI in education, particularly for educational opportunities outside the classroom. Modern chatbots are already very efficient in their processing and can answer student questions at a response rate of 2.7 seconds. Companies like Capacity and AllHere have already developed conversational AI tools to answer student queries related to subjects and internal university matters such as assignments and exams.

A study conducted on Ghanaian students revealed that students that interacted with an educational chatbot scored 25% higher than those that did not.

Improved testing, grading, and assessment
We have talked about how educational chatbots can deliver feedback on answers and queries to improve student outcomes. The same models can be used for automated testing systems. AI-based assessment involves a combination of vision and language-based models to capture test information, understand it, and output a grade accordingly.

Vision-based grading
Computer vision-based tools such as GradeScanner use images of bubble sheets to score multiple-choice questions automatically. Other uses of computer vision for grading include using tools like MS Maths to score mathematics-related questions using images of the equations. These methods of grading can save teachers time and reduce errors.

Source: GradeScanner
Language-model-based grading
AI can understand the written text from essays or long-form answers, map it to traditional grade levels and create a score for the writing. Several educational organizations, such as Pearsons and Educational Testing Service, use AI language models to help score essays. Other uses of AI in education grading include plagiarism detection by services like Turnitin.

Automation of administrative tasks
77% of teachers feel they cannot do their best work because of a lack of time and resources. Grading assignments for a single class require teachers to carefully go through each submission which can take up to several hours. This takes away time from the teachers that they could otherwise use to work with the students.

AI graders are efficient enough to slash grading times by 90% and have cut the overall grading process time by 50%.

For example, artificial intelligence can provide universities with smart student enrolment methodologies. Most institutes review each enrollment application manually, filter out suitable candidates and approve scholarships or financial aid. AI predictive systems can help target potential candidates and automate tasks of application review. A private, mid-sized university was reported to have increased its enrolment yield by 15% by adopting Aible's AI system.

Besides enrolment, institutes and states still have to deal with thousands of student-related documents, such as grade sheets, applications, and performance reviews. For instance, the state of Nebraska reported spending approximately 655,000 staff hours per year to collect data reports from every school in the territory. The introduction of AI for task automation digitizes the document-handling process. This creates a network of education-related files and reports in a big data architecture, which can be accessed by any authorized institute and further used for processing.

Document processing using AI has been around for several years and automates the entire information processing cycle. V7's document processing engine delivers an accuracy of 99% for identifying key text fields and automates end-to-end workflows for data handling and document storage.

Final thoughts
AI in education delivers an enhanced experience for both students and teachers. It offers several benefits, including improved accessibility, tutoring, automated grading and administration, and streamlined workflows. These provide students with high-quality education and relieve teachers of fatigue.

Many institutes around the world already leverage AI to automate processes and deliver efficient education. However, certain standards would have to be met for wider adoption. AI models are prone to errors, and this can be damaging to students learning. Furthermore, ethical guidelines must be formed to ensure that models do not display biases while teaching and grading and that the educational material is not harmful to any community.

💡 Read next: