another post for students in data analytics In the exciting world of data analytics, we often hear about cutting-edge algorithms, sophisticated visualizations, and the power of data-driven decision-making. However, lurking beneath the surface of every successful analysis is a less glamorous but essential process: data cleaning. You might be eager to jump straight into uncovering Read More
Author: Gary Ackerman
Variance vs. Standard Deviation
A post for students in data analytics: Variance and standard deviation are both measures of dispersion used in data analysis, but they differ in their calculation, interpretation, and application. Here’s a breakdown of the key differences: Definition Calculation Units Interpretation Application to Normal Distribution In summary, while both variance and standard deviation measure the spread Read More
Encryption
A post for network security students: In today’s digital age, encryption is a cornerstone of cybersecurity, safeguarding our data from prying eyes. Encryption is the art and study of writing codes. It involves transforming plaintext (readable data) into ciphertext (encrypted data) using ciphers and cryptographic algorithms. Encryption ensures that only authorized individuals can decipher and Read More
Elevator Pitches on Deeper Learning
Deeper learning refers to an approach to education that aims to equip students with the skills needed to deal with complexity and solve real-world problems. It goes beyond memorizing facts and focuses on competencies like problem-solving, critical thinking, collaboration, effective communication, learning how to learn, and developing an academic mindset. It’s important because traditional education Read More
Social Engineering
IIn the realm of cybersecurity, reverse engineering stands as a powerful technique used to dissect and understand the inner workings of software, hardware, or any system, without access to its original design or source code. By meticulously examining the final product, cybersecurity analysts can uncover vulnerabilities, analyze malware, and enhance security measures. What is Reverse Read More
Denial of Service Attacks
A post for network security students: In today’s interconnected digital landscape, maintaining the availability of systems and networks is paramount. One of the most prevalent threats to availability is the Denial-of-Service (DoS) attack, which aims to overwhelm a system with malicious traffic, rendering it inaccessible to legitimate users. Understanding DoS attacks and implementing effective prevention Read More
On Professional Development Models for #edtech
Recognizing that teachers are flexible professionals who specialize in using technology to support teaching and learning require on-going opportunities for professional learning is essential for school and technology leaders. This professional learning will be characterized by a mix of self-selected and self-defined learning (based on one’s expertise and understanding of current need) and new ideas, Read More
Social Influences on Technology Decisions
Educators are social beings (just as all humans are) and so the social environment in which they live and work is meaningful and influences their intentions and their behaviors. When school and technology leaders take steps to ensure that individuals perceive other individuals (especially those who are respected and perceived to be doing similar work) Read More
Penetration Testing
Another post for network security students: Penetration testing is a simulated attack against an organization using the same information, tools, and techniques available to real attackers. During a penetration test, testers seek to gain access to systems and information and then report their findings to management. The results of penetration tests may be used to Read More
Data Wrangling
Another post for data analytics students… Data wrangling, also known as data manipulation, is the process of preparing data for use, ensuring it’s in a specific shape or format that applications can utilize. It involves skillfully handling and managing data to make it usable for analysis. Methods for data wrangling include: • Merging data—Combining datasets Read More