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Essential UX Practices for Ed-tech

The slingshot effect of COVID-19 on distance learning contributed to the ed-tech boom in 2020–2022. Keeping an optimal user experience became crucial for ed-tech rivals to obtain a maximum user base and supply high-quality learning solutions to learners. This was due to the huge volume of tech goods on websites and apps aiming to impart education. Due to the remarkable changes in career opportunities and the need for upskilling for them, the trend of remote education is still popular and in great demand. This trend is especially evident in upskilling and test preparation. And there is increased demand to maintain a good user experience with ed-tech products. Here are some essential UX practices for Ed-tech:

  1. Accessibility:
    It is crucial to make sure that all users, including those with disabilities, can access ed-tech platforms. This includes tools like text-to-speech choices, closed captioning, and screen readers. Additionally, a user-friendly interface should be included in the platform’s architecture. This makes it simple for users to explore and locate the data they require. One example below about accessibility:
Legends (for those without complete color blindness)
Legends Appearance (for those without color blindness) 
Legends (for those with complete color blindness)
Legends (for those with complete color blindness)

The above picture is an interface design for the nationally adopted format of the online examination. It has been designed to make the system accessible for people with color blindness (1 of every 12 people in the world is color blind). With the help of the legends, the students navigate questions with color and shape recognition. Observe the shape and color used for ‘answered’ and ‘not answered’ which are in green and red, respectively. If the shape had not been different, it would have been difficult for a student with color blindness to recognize which question is answered, which one is not, and which question is marked for review. Different shapes break the consistency in design elements as per some UI design rules, but this is necessary due to accessibility.

Legends with different shapes and colors
Legends with uniform shapes and different colors (visibility without and with colorblindness, respectively)
Legends with different shapes and colors
Legends with different shapes and different colors (visibility without and with colorblindness, respectively)
  1. Personalization:
    Our learning at school was organic and nurturing due to the personal connection each student had with the teachers. When we talk about education, there should be a personal connection between the students and the system to boost students’ learning. Platforms for ed-tech should be created to meet the behavior and demands of every student. This entails tailoring feedback, designing a learning path specifically for each student, and personalizing the educational experience. This strategy boosts student enthusiasm and engagement, which will result in better learning outcomes.
  1. Gamification:
    Gamification has been one of the most important and essential UX practices in ed-tech and education. By adding game-like components like incentives, points, and badges, gamification techniques can be utilized to improve the learning experience. Learning can become more enjoyable and interesting as a result, especially for younger children.
  1. Collaboration and feedback:
    Edtech platforms should make it easier for students and teachers to collaborate, as it is a crucial component of the learning process. Features like collaborative projects, discussion boards, and video conferencing fall under this category.
    Giving feedback on time is essential for the learning process. Platforms for education technology should provide feedback on students’ progress along with suggestions for what might be done better. Students who are driven and interested in their studies may benefit from this. While building an ed-tech platform, it’s crucial to build features for smooth collaboration among learners, educators, and administration. 
  1. Mobile optimization:
    Ed-tech platforms should be mobile-optimized given the rising use of mobile devices. This entails creating an interface that is appropriate for mobile use, providing mobile-specific functionality, and making sure the platform is usable on a range of devices.
    Note: Soon an upcoming blog will have a detailed view of “mobile optimization” in ed-tech. Keep reading Mantra Labs’ blog post.
  1. Data analytics:
    Data analytics systems for ed-tech platforms should be able to monitor student progress, pinpoint areas for development, and give teachers feedback. This can assist teachers in modifying their instruction to better meet the needs of each student.
  1. Continuous improvement:
    Last but not least, ed-tech platforms must be created with ongoing improvement in mind. This includes ongoing upgrades and enhancements based on user input and the most recent developments in ed-tech. Platforms should be built with scalability in mind so that they may change and evolve as requirements do. The Design Thinking process will help in creating such a system that will help students, teachers, and the company from all angles in this situation by making, remaking, and continuously refining the system.

Key takeaways:

  1. Prioritize accessibility and personalization to create a user-friendly learning experience for all students.
  2. Personalization in design creates strong and nurturing connections between the system and students.
  3. Incorporate gamification to increase student engagement and motivation.
  4. Provide collaboration and feedback features to improve engagement in the learning process.
  5. Optimize ed-tech platforms for mobile use to cater to the growing use of mobile devices.
  6. Utilize data analytics to track student progress and identify areas for improvement.
  7. Continuously improve ed-tech platforms based on user feedback and the latest industry trends.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UX Research and Product Design.

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10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

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