In modern online learning, understanding and predicting student behavior is crucial for enhancing engagement and optimizing educational outcomes. This systematic review explores the integration of biosensors and Multimodal Learning Analytics (MmLA) to analyze and predict student behavior during computer-based learning sessions. We examine key challenges, including emotion and attention detection, behavioral analysis, experimental design, and demographic considerations in data collection. Our study highlights the growing role of physiological signals, such as heart rate, brain activity, and eye-tracking, combined with traditional interaction data and self-reports to gain deeper insights into cognitive states and engagement levels. We synthesize findings from 54 key studies, analyzing commonly used methodologies such as advanced machine learning algorithms and multimodal data pre-processing techniques. The review identifies current research trends, limitations, and emerging directions in the field, emphasizing the transformative potential of biosensor-driven adaptive learning systems. Our findings suggest that integrating multimodal data can facilitate personalized learning experiences, real-time feedback, and intelligent educational interventions, ultimately advancing toward a more customized and adaptive online learning experience.

One of the strengths of local AI is its ability to filter out unwanted noise, and a couple of new Windows features Microsoft is testing take advantage of that. One of them will be rolled out to Copilot PCs that use Intel processors first, breaking Microsoft's streak of tying new features to Windows on Qualcomm Snapdragon processors. The feature promises to correct grammar and punctuation, as well as to get rid of what's known as "filler words:" the "you know," "um," and "well," words that many people add as they internally parse their thoughts into a coherent sentence. The other new feature is a key addition for webcams, as well. If you own a Copilot PC, you may have noticed Windows Studio Effects kick in while using the webcam: the webcam automatically crops in on your face, "zooming" to frame it in the picture.

Over the past decade, the demand for communication devices has increased among individuals with mobility and speech impairments. Eye-gaze tracking has emerged as a promising solution for hands-free communication; however, traditional appearance-based interfaces often face challenges such as accuracy issues, involuntary eye movements, and difficulties with extensive command sets. This work presents a multimodal appearance-based gaze-controlled virtual keyboard that utilises deep learning in conjunction with standard camera hardware, incorporating both synchronous and asynchronous modes for command selection. The virtual keyboard application supports menu-based selection with nine commands, enabling users to spell and type up to 56 English characters, including uppercase and lowercase letters, punctuation, and a delete function for corrections. The proposed system was evaluated with twenty able-bodied participants who completed specially designed typing tasks using three input modalities: (i) a mouse, (ii) an eye-tracker, and (iii) an unmodified webcam. Typing performance was measured in terms of speed and information transfer rate (ITR) at both command and letter levels. Average typing speeds were 18.3+-5.31 letters/min (mouse), 12.60+-2.99letters/min (eye-tracker, synchronous), 10.94 +- 1.89 letters/min (webcam, synchronous), 11.15 +- 2.90 letters/min (eye-tracker, asynchronous), and 7.86 +- 1.69 letters/min (webcam, asynchronous). ITRs were approximately 80.29 +- 15.72 bits/min (command level) and 63.56 +- 11 bits/min (letter level) with webcam in synchronous mode. The system demonstrated good usability and low workload with webcam input, highlighting its user-centred design and promise as an accessible communication tool in low-resource settings.

The best webcam makes you look your best -- for less. Most laptops ship with a 720p webcam, so a 1080p webcam or even a 4K webcam can make you stand out by comparison. I haven't tested every one of these webcams, just most of them -- and I describe how I test under my recommendations. You can also refer to my separate story on the best Windows Hello webcams for recommendations that aid videoconferencing and log you into your PC. Two recommendations from that list -- a premium and budget option -- appear on this list. Why you should trust me: PCWorld has been testing PC hardware since the 1980s, and I've been a technology journalist for 30 years, with extensive experience in reviewing PC hardware. When it comes to webcams, my recommendations are based on hands-on testing in real-world scenarios. I also tap the expertise and published reviews of my counterparts in Sweden and Germany to offer a comprehensive view of the current webcam landscape. The Anker PowerConf C200 offers an affordable yet substantial upgrade from the 720p cameras found in most laptop webcams to a 1440p webcam, yet does so at an affordable price.

Some of the best tech we see at CES feels pulled straight from sci-fi. Yesterday at CES 2025, I tested out Neural Lab's AirTouch technology, which lets you interact with a display using hand gestures alone, exactly what movies like Minority Report and Iron Man promised. Of course, plenty of companies have delivered on varying forms of gesture control. Microsoft's Kinect is an early example while the Apple Watch's double tap feature and Vision Pro's pinch gestures are just two of many current iterations. But I was impressed with how well AirTouch delivered and, unlike most gesture technology out there, it requires no special equipment -- just a standard webcam -- and works with a wide range of devices.

Domain adaptation (DA) tackles the issue of distribution shift by learning a model from a source domain that generalizes to a target domain. However, most existing DA methods are designed for scenarios where the source and target domain data lie within the same feature space, which limits their applicability in real-world situations. Recently, heterogeneous DA (HeDA) methods have been introduced to address the challenges posed by heterogeneous feature space between source and target domains. Despite their successes, current HeDA techniques fall short when there is a mismatch in both feature and label spaces. To address this, this paper explores a new DA scenario called open-set HeDA (OSHeDA). In OSHeDA, the model must not only handle heterogeneity in feature space but also identify samples belonging to novel classes. To tackle this challenge, we first develop a novel theoretical framework that constructs learning bounds for prediction error on target domain. Guided by this framework, we propose a new DA method called Representation Learning for OSHeDA (RL-OSHeDA). This method is designed to simultaneously transfer knowledge between heterogeneous data sources and identify novel classes. Experiments across text, image, and clinical data demonstrate the effectiveness of our algorithm. Model implementation is available at \url{https://github.com/pth1993/OSHeDA}.

I review a lot of home office gear for my job, which means my workstation is in flux. A new desk today, another office chair tomorrow--you get the idea. You may have heard of BenQ before--the Taiwanese company makes excellent monitors and projectors--but this lamp is my number one work-from-home accessory. The ScreenBar doesn't take up any desk space, because it hangs over your computer monitor and brilliantly illuminates the desktop. It's a simple little thing, but it brings me a lot of joy, and the company has been iterating on it, with the latest version being the ScreenBar Pro. I'm here to tell you that you should probably get one for your home office.

I made a joke earlier this week in my family group chat that everybody was getting 2 and a macaroni picture frame for Christmas. But seriously, have you seen those grocery store prices? I'm shopping for 20 people, and my bank account is already wincing. Luckily, with these Cyber Monday deals under 50, holiday shopping doesn't have to be pricey. We've rounded up deals on affordable tested-and-approved gear so you can get your shopping done without crying afterward. Make sure you check out our live Cyber Monday deals tracker here. For under 20, this Arlo camera streams crisp 1080p video straight to your smartphone and even includes motion detection alerts and two-way communication to check in on pets. Whether mounted on a wall or tucked on a shelf, it's also a stealthy security spy. With an 8/month subscription, you'll also get extra features like cloud storage. The Roku Streaming Stick 4K is a small upgrade with a game-changing payoff. An intuitive interface, customizable home screen, and access to a variety of free channels--what more could you ask for? No wonder it is our favorite Roku device and overall streaming device.

The Coolpo AI Huddle Mini Lite is a unique, laptop-mounted webcam that can be used either for individual use or a small group. It largely delivers what it promises, with one significant exception. Coolpo's AI Huddle Mini Lite does double duty as an individual webcam and one that can show off a number of participants in the same room, in a pinch. It's a smartly designed "4K" camera, which foregoes frills for a simple, easy-to-use interface. Coolpo is one of those hundreds of little startups in Shenzhen, China, whose products come and go quickly.

The big Windows 11 2024 Update (also known as Windows 11 24H2) is both a brand-new operating system but also one that's been out for several months now. And its best features are really reserved for those who have invested in a next-gen Copilot PC powered by chips from Qualcomm, Intel, and AMD. These seeming contradictions are at the heart of Windows 11 24H2, which begins rolling out today in a "phased" rollout that will last several weeks. But when you get it and what you get with it will all depend on whether you own a Copilot PC. In other words, there's a set of basic features that everyone will receive (including new energy-saving features for laptops and desktops, improved smartphone integration, plus support for Wi-Fi 7 and the upgraded 80Gbps capabilities of USB4), along with more advanced features that are only available to Copilot PC users.