Online studying offers numerous benefits. You get to learn at your own pace (from the comfort of your home), access significantly more resources, and manage your schedule. But that last part isn’t always easy.

When left to your own devices, you might start procrastinating and losing track of time. Then, before you know it, finals are approaching, and you’re nowhere near prepared.

Luckily, we have a solution for this common challenge here at the Open Institute of Technology (OPIT)—or two solutions, to be precise.

One, there are no finals. You’re continually assessed by the incredible faculty, pushing you to engage with the material throughout the course. And two, OPIT’s amazing class coordinator, Sara Ciabattoni, is here to help you overcome specific challenges with procrastination and other issues (e.g., complex and overwhelming tasks).

For this guide, we asked Sara to share her top 10 time management tips. Since time is money, let’s dive in!

1. Reflect on Your Current Time Management Approach

Do you constantly feel overwhelmed and fail to keep up with your tasks? If so, something’s not working. It’s probably time to reassess your approach to time management. And by this, Sara doesn’t just mean your studying time. Instead, she implores you to reflect on how you usually manage time in your everyday life.

Become aware of your time management habits (both good and bad), and a more effective approach to studying is right around the corner.

Let’s say you excel at focusing in the morning but find it difficult to do so in the afternoon. In that case, leave your most demanding study tasks for the morning, aka your peak focus hours. The more time passes, the less complex your tasks should be.

Similarly, if you tend to procrastinate, your goal is to answer a single question – why?

Sometimes, the cause is something silly, such as the so-called FOMO (Fear of Missing Out), which keeps you glued to your screen. In other situations, the cause might be more serious (e.g., an innate fear of failure). Whatever the case, address these underlying issues promptly, as this is the only way to make the most out of your study time.

2. Create a Manageable Routine

No one can do it all at once (And no one should!). So, start by making a list of priorities and turning them into a to-do list. Make seven to-do lists, and you have a manageable weekly schedule that suits your day-to-day life.

If you struggle with prioritizing tasks, you can use the ABC method. Here’s an example to help you visualize this method in practice.

Let’s say you’re pursuing a Bachelor’s Degree (BSc) in Modern Computer Science at OPIT. The elective “Agile Development and DevOps” subject teaches you to implement software projects successfully.

For this subject, an “A” task would be to prepare for a specific real-world scenario developers encounter every day. You’ll experience several of these valuable and time-sensitive scenarios, making them tasks of the highest priority.

For a “B” task, you can practice using Microsoft Azure. This task is important but not as urgent as your “A” task.

Finally, a “C” task can entail working on your negotiation skills to help you convince team members to adopt a specific DevOps methodology. As you can probably guess, “C” tasks are tasks of lower priority, usually because they’re less time-sensitive.

3. Introduce Variety

Sure, this tip doesn’t directly impact your time management. However, it does play a huge role in whether you’ll stick to your studying routine.

If you always study in the same place and in the same way, you’re bound to get bored and lose motivation. So, try mixing things up a little.

For instance, instead of re-reading the course materials over and over again to memorize them, try turning them into a flowchart or a mind map. These handy visual tools can help you grasp concepts differently and make studying more engaging.

4. Take Advantage of All the Available Resources

OPIT prides itself on the wealth of resources available to students, each crafted from scratch. But these resources aren’t only concerned with studying. The OPIT Hub also contains helpful tools you can use to navigate your online studying journey.

One of these resources is a weekly planner designed to turn your priorities into a manageable weekly schedule. Like everything at OPIT, this planner is highly customizable, allowing you to tailor it to your unique needs and preferences.

5. Connect With Others

At OPIT, we also set priorities. One of them is for our students to never feel alone. That’s why we offer an extensive support network to ensure you always have someone to turn to.

So, don’t hesitate to ask for help if you feel stuck or lost. Besides OPIT’s staff, you should connect with your peers and even form online study groups. This will help you keep up with your tasks in a more collaborative and supportive environment. And hey – you might even get to make new friends from all over the world!

6. Don’t Forget About Downtime

Creating a solid schedule isn’t about filling every available moment with a task. Sure, it’s important to get your work done. However, it’s equally crucial to prevent burnout. How can you do this? By including downtime in your schedule.

Of course, you can use your downtime however you see fit. But Sara suggests spending it with your loved ones whenever possible. This will boost your mood and overall well-being, making subsequent studying a breeze. It will also help you achieve the most coveted of all goals – a healthy work-life balance.

But don’t forget – “work” is still a key element of this balance. So, make sure the people in your life also know your schedule (and are willing to respect it).

7. Never Sacrifice Your Basic Needs

Sure, it might seem to you that you’ll get more done if you wake up super early. But this couldn’t be further from the truth. Failing to get enough sleep can only make you less productive, both that day and in the long run.

So, make sure you leave enough time for a good night’s sleep in your schedule. For the best possible results, aim for seven to nine hours.

8. Avoid Jam-Packing Your Schedule

When it comes to estimating how much time you need to allocate for a specific task, remember this – it’s better to be safe than sorry.

Overestimating the time you’ll need for a complex task trumps underestimating every single time. Why? If you underestimate the time you’ll need to complete a task, you’ll feel extremely stressed upon realizing that your deadline is approaching and the work is not yet completed. This will cause you to fall behind on your entire schedule or, even worse, rush through work and compromise its quality.

Overestimating, on the other hand, provides a safety net for unforeseen challenges. Finish the task(s) before the allocated time, and you’ll feel a sense of accomplishment like no other! But it’s OK even if you don’t, as there’s enough time for everything.

Another approach you can take is to break larger tasks into smaller, more manageable chunks. Then, you can allocate a shorter amount of time to each sub-task and feel great when you get it done.

9. Be Kind to Yourself

You can devise the perfect studying plan for the week with enough room for studying, revising, and relaxing. You can even go into the week refreshed, ready to take on any challenge. And yet, it can all fall apart the second that week begins. And that’s OK!

Some days just don’t go as planned. You might receive some bad news or encounter unexpected challenges that disrupt your schedule.

So, be kind to yourself if you’re going through one of these days. Remember that the day will pass just as quickly as it came, and you’ll be back on track in no time.

10. Measure (and Celebrate) Your Progress

How can you tell whether your schedule is truly working? By measuring your progress, of course! Format every task as a SMART goal, and you’ll always know where you stand.

Let’s see what this means using another subject at OPIT – “Web Development.”

  • Specific: “I will learn to create a domain hosting comparison report.”
  • Measurable: “I will create at least three reliable reports.”
  • Attainable: “I have already received the theoretical knowledge necessary for this task.”
  • Relevant: “Creating these reports will enhance my understanding of existing domain host options.”
  • Time-bound: “I will complete the three reports by the end of the week.”

If you succeed in completing these reports by the end of the week, give yourself a little reward. It’s crucial for you to celebrate your progress, no matter how small or big. This is the only way to stay motivated in the long run and maintain a positive mindset throughout your academic journey at OPIT.

There’s No One-Size-Fits-All Solution

When it comes to student support, OPIT emphasizes a personal approach to every student. That’s why it’s crucial to remember that no single time management solution will help all students. After all, each student faces specific challenges, leads a unique lifestyle, and has an individual learning style.

However, as long as you combine Sara’s tips with methods that have proven successful for your specific circumstances (and preferences), you should have no issue excelling at online studying.

 

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Agenda Digitale: AI Ethics Starts with Data – The Role of Training
OPIT - Open Institute of Technology
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May 20, 2025 6 min read

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By Riccardo Ocleppo, Founder and Director of OPIT – Open Institute of Technology

AI ethics requires ongoing commitment. Organizations must integrate guidelines and a corporate culture geared towards responsibility and inclusiveness, preventing negative consequences for individuals and society.

In the world of artificial intelligence, concerns about algorithmic bias are coming to the forefront, calling for a collective effort to promote ethical practices in the development and use of AI.

This implies the need to understand the multiple causes and potential consequences of the biases themselves, identify concrete solutions and recognize the key role of academic institutions in this process.

Bias in AI is a form of injustice, often systemic, that can be embedded in algorithms. Its origins are many, but the main culprit is almost always the data set used to train the models. If this data reflects inequalities or prejudices present in society, the risk is that AI will absorb and reproduce them, consolidating these distortions.

But bias can also manifest itself in the opposite direction. This is what happened some time ago with Google Gemini. The generative AI system developed by Google, in an attempt to ensure greater inclusivity, ended up generating content and images completely disconnected from the reality it was supposed to represent.

Further complicating the picture is the very nature of AI models, which are often characterized by complex algorithms and opaque decision-making processes. This complexity makes it difficult to identify, and therefore correct, biases inherent in the systems.

Ethical Data Management to Reduce Bias in AI

Adopting good data management practices is essential to address these issues. The first step is to ensure that the datasets used for training are diverse and representative. This means actively seeking data that includes a wide variety of demographic, cultural, and social contexts, so as to avoid AI exclusively reproducing existing and potentially biased models.

Alongside data diversification, it is equally important to test models on different demographic groups. Only in this way can latent biases that would otherwise remain invisible be highlighted. Furthermore, promoting transparency in algorithms and decision-making processes is crucial. Transparency allows for critical control and makes all actors involved in the design and use of AI accountable.

Strategies for ethical and responsible artificial intelligence

Building ethical AI is not an isolated action, but an ongoing journey that requires constant attention and updating. This commitment is divided into several fundamental steps. First, ethical guidelines must be defined. Organizations must clearly establish the ethical standards to follow in the development and use of AI, inspired by fundamental values ​​such as fairness, responsibility and transparency. These principles serve as a compass to guide all projects.

It is also essential to include a plurality of perspectives in the development of AI. Multidisciplinary teams, composed of technologists, ethicists, sociologists and representatives of the potentially involved communities, can help prevent and correct biases thanks to the variety of approaches. Last but not least, promote an ethical culture : in addition to establishing rules and composing diverse teams, it is essential to cultivate a corporate culture that places ethics at the center of every project. Only by integrating these values ​​​​in the DNA of the organization can we ensure that ethics is a founding element of the development of AI.

The consequences of biased artificial intelligence

Ignoring the problem of bias can have serious and unpredictable consequences, with profound impacts on different areas of our lives. From the reinforcement of social inequalities to the loss of trust in AI-based systems, the risk is to fuel skepticism and resistance towards technological innovation. AI, if distorted, can negatively influence crucial decisions in sectors such as healthcare, employment and justice. Think, for example, of loan selection algorithms that unfairly penalize certain categories, or facial recognition software that incorrectly identifies people, with possible legal consequences. These are just some of the situations in which an unethical use of AI can worsen existing inequalities.

University training and research to counter bias in AI

Universities and higher education institutions have a crucial responsibility to address bias and promote ethical practices in AI development. Ethics must certainly be integrated into educational curricula. By including ethics modules in AI and computer science courses, universities can provide new generations of developers with the tools to recognize and address bias, contributing to more equitable and inclusive design. Universities can also be protagonists through research.

Academic institutions, with their autonomy and expertise, can explore the complexities of bias in depth, developing innovative solutions for detecting and mitigating bias. Since the topic of bias is multidimensional in nature, a collaborative approach is needed, thus fostering interdisciplinary collaboration. Universities can create spaces where computer scientists, ethicists, lawyers, and social scientists work together, offering more comprehensive and innovative solutions.

But that’s not all. As places of critical thinking and debate, universities can foster dialogue between developers, policy makers, and citizens through events, workshops, and conferences. This engagement is essential to raise awareness and promote responsible use of AI.

In this direction, several universities have already activated degree courses in artificial intelligence that combine advanced technical skills (in areas such as machine learning, computer vision and natural language processing) with training that is attentive to ethical and human implications.

Academic Opportunities for an Equitable AI Future

More and more universities around the world – including Yale and Oxford – are also creating research departments dedicated to AI and ethics.

The path to ethical AI is complex, but it also represents an opportunity to build a future where technology truly serves the common good.

By recognizing the root causes of bias , adopting responsible data practices, and engaging in ongoing and vigilant development, we can reduce the unintended effects of biased algorithms. In this process, academic institutions – thanks to their expertise and authority – are at the forefront, helping to shape a more equitable and inclusive digital age.

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TechFinancials: Are We Raising AI Correctly?
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 20, 2025 5 min read

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By Zorina Alliata

Artificial intelligence (AI) used to be the stuff of science fiction. Stories about rogue machines and robot uprisings were once a source of amusement, not anxiety. But over recent years, AI has quietly embedded itself in our daily lives.

From the algorithms behind social media feeds, to the voice assistants managing our calendars. This quiet takeover has become something far louder: fear.

Headlines around AI are often alarmist. Statements such as “AI will take your job”, “AI will end education”, or “AI is dangerous and unregulated” are thrown around regularly. These narratives feed on uncertainty and fuel distrust.

But it doesn’t have to be this way. The hyper-fixation on the never-ending negative aspects of AI is the wrong approach to take. What if AI isn’t the villain? What if, at this stage, it’s simply a child?

AI, in many ways, is still learning. It mimics human behaviour, absorbs language, and forms patterns based on what it sees. Its current capabilities, however powerful they may seem, are not equivalent to human intelligence. It has limitations. It makes mistakes. It can even be manipulated and misled. It reflects our world; flaws and all. In that sense, AI is less an omnipotent force and more in line with a toddler trying to find its way.

And, like any child, it needs guidance.

This is especially evident in education. The emergence of AI tools such as ChatGPT has caused a stir in higher education institutions and universities, sparking fears about plagiarism and the erosion of critical thinking. Some institutions have responded with strict bans, while others have embraced cautious integration. The panic is understandable, but is it misplaced?

Rather than jumping to conclusions, educators should consider shifting the conversation. AI can, in fact, become an ally in learning. Instead of assuming students will cheat, we can teach them to use AI responsibly. Most of us educators can already recognise the signs of AI-generated work: excessive use of numbered lists, repetitive language and poor comparison skills. So why not use this as a teaching opportunity?

Encouraging students to engage with AI critically, understanding what it’s good at, where it falls short, and how to improve its output, can strengthen their own analytical skills. It invites them to become more active participants in their learning, not passive consumers of machine generated answers. Teaching young people how to work with AI is arguably more important than shielding them from it.

Outside the classroom, AI’s impact on the workforce is another growing concern. Stories about AI replacing jobs often dominate the news cycle. But these conversations often ignore a key point: AI is not autonomous. AI needs human designers, engineers, analysts, and ethicists to guide it. For every job that AI may eliminate, others will emerge to support and direct it.

More importantly, there are many things AI simply cannot do. It doesn’t understand nuance, morality or emotion. It can’t make ethical decisions without human input. These aren’t minor gaps, they’re fundamental. That’s why we must stop imagining AI as an unstoppable force and start thinking about how to raise it responsibly.

When considering how to raise our AI child responsibly, we need to acknowledge the issue of the algorithm being biased. Critics often point out that AI reproduces prejudices and errors, and whilst this is true, the source of that bias is us. It is important to remember that AI learns from historical data created by us, much of which reflects deeply ingrained societal inequalities.

Take, for example, mortgage lending in the US, where decades of discriminatory practices have skewed the data. Unless we intervene, AI trained on this information will inevitably reflect those same biases.

That’s not a reason to reject AI. It’s a reason to be more involved in its development, like any good parent. The responsibility lies with us.

Parenting is not about control for control’s sake; it’s about nurturing growth while setting boundaries. AI, like a child, needs feedback, accountability, and care. It will grow, but how it grows is up to us.

It’s tempting to view technology as something that happens to us, rather than something we can shape. But AI doesn’t exist outside of society, it’s a product of our values, decisions, and input. If we treat it as a monster, it may become one. If we treat it as a mirror, it will reflect what we show it. And if we treat it as a child, we may be able to raise it into something better.

So instead of fearmongering, let’s ask ourselves a better question: Are we raising AI correctly?

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