Comparing collaborative problem solving in virtual reality and desktop computer display environments

https://www.ester.ee/record=b5160211*es

Pengaturan level kesulitan pada game edukasi bencana gunung meletus menggunakan metode Markov Chain

Indonesia: Indonesia merupakan negara yang rawan bencana. Salah satunya adalah letusan gunung berapi yang menimbulkan banyak korban akibat bencana tersebut, dalam hal ini pendidikan pencegahan bencana harus dikenalkan sejak dini termasuk anak sekolah dasar. Saat ini media edukasi yang mempromosikan kemandirian dan keselamatan anak sekolah dasar dalam situasi krisis masih sangat minim. Kurangnya media pelatihan untuk mengenali, mencegah atau melarikan diri dari situasi berbahaya dan keterampilan komunikasi untuk melaporkan situasi ketika muncul. Dengan pesatnya perkembangan teknologi, game menjadi salah satu teknologi yang paling populer saat ini. Oleh karena itu, perlu adanya permainan edukatif yang menggabungkan mitigasi berupa simulasi dan informasi mitigasi bencana. Game yang dibuat ini menggunakan metode Markov Chain yang di bantu dengan Dynamic Difficulty Adjustment untuk pengaturan kesulitan level kabut yang disusuaikan dengan kemampuan pemain. Data masukan pada game ini terdapat 7 variabel diantaranya skor, waktu, darah pemain, jumlah barang, tipe barang, jumlah musuh dan tipe musuh. Setelah didapatkan nilai dari masing masing variabel. Kemudian data tersebut akan di oleh menggunakan metode Markov Chain untuk medapatkan keluaran berupa level. Pada skenario pengujian 2 dengan menetapkan variabel bebas pada nilai time (50,75,90,100,110,130,146,150 dan 160) memberikan hasil paling tinggi untuk diversifikasi pengaturan level kesulitan pada game edukasi bencana gunung meletus yaitu 2,5 kali. Bahwa penerapan metode Markov Chain pada game edukasi bencana gunung meletus ini tidak memberikan hasil berupa penigkatan diversifikasi level kesulitan. English: Indonesia is a disaster-prone country. One of them is the volcanic eruption which caused many victims as a result of the disaster, in this case disaster prevention education must be introduced from an early age, including elementary school children. Currently educational media that promote independence and safety of elementary school children in crisis situations are still very minimal. Lack of media training to recognize, prevent or escape from dangerous situations and communication skills to report situations when they arise. With the rapid development of technology, games have become one of the most popular technologies today. Therefore, there is a need for educational games that combine mitigation in the form of simulations and information on disaster mitigation. This game is made using the Markov Chain method which is assisted by Dynamic Difficulty Adjustment for fog level difficulty settings that are adjusted to the player's abilities. Input data in this game there are 7 variables including score, time, player blood, number of items, type of item, number of enemies and type of enemy. After obtaining the value of each variable. Then the data will be processed using the Markov Chain method to get output in the form of levels. In test scenario 2 by setting the independent variable at the time value (50,75,90,100,110,130,146,150 and 160) gave the highest results for diversification of difficulty level settings in the volcanic eruption disaster educational game, namely 2.5 times. That the application of the Markov Chain method to this volcanic eruption disaster educational game did not produce results in the form of increasing diversification of difficulty levels. Arabic: وإندونيسيا بلد معرض للكوارث. واحد منهم هو الجبل المندلع ، حيث يوجد العديد من الضحايا بسبب الكارثة ، وفي هذه الحالةي جب إدخال التعليم حول التخفيف من حدة الكوارث منذ سن مبكرة ، بما في ذلك لطلاب المدارس الابتدائية. في الوقت الحاضر ، لا تزال وسائل الإعلام التعليمية لتعزيز الاستقلال والسلامة في حالات الطوارئ لطلاب المدارس الابتدائية تفتقر إلى حد كبير. عدم وجود وسائل إعلام تعليمية للتعرف على المواقف الخطرة أو منعها أو إنقاذها ، وكذلك مهارات الاتصال للإبلاغ عن المواقف في حالة حدوثها. فيما يتعلق بالتطور السريع للتكنولوجيا ، أصبحت الألعاب واحدة من التقنيات الشائعة في هذا العصر. لذلك ، من الضروري أن يكون لديك لعبة تعليمية تحتوي على التخفيف في شكل محاكاة ومعرفة حول التخفيف من حدة الكوارث. يتوقع المجتمع من الألعاب كوسيلة للنهج ، وخاصة الطلاب الأساسيين ، أن يكونوا قادرين على التعرف على التهديدات والآثار المختلفة للكارثة الجبلية المندلعة والتغلب عليها. تستخدم هذه اللعبة طريقة Markov Chain التي يساعدها ضبط الصعوبة الديناميكي لتحديد صعوبة مستويات الضباب التي يتم ضبطها وفقا لقدرات اللاعب. تحتوي بيانات الإدخال في هذه اللعبة على 7 متغيرات بما في ذلك النتيجة والوقت ودم اللاعب وعدد العناصر ونوع السلع وعدد الأعداء ونوع العدو. بعد الحصول على قيمة كل متغير. ثم سيتم الحصول على البيانات باستخدام طريقة سلسلة ماركوف للحصول على المخرجات في شكل مستويا

Affective state recognition in Virtual Reality from electromyography and photoplethysmography using head-mounted wearable sensors.

The three core components of Affective Computing (AC) are emotion expression recognition, emotion processing, and emotional feedback. Affective states are typically characterized in a two-dimensional space consisting of arousal, i.e., the intensity of the emotion felt; and valence, i.e., the degree to which the current emotion is pleasant or unpleasant. These fundamental properties of emotion can not only be measured using subjective ratings from users, but also with the help of physiological and behavioural measures, which potentially provide an objective evaluation across users. Multiple combinations of measures are utilised in AC for a range of applications, including education, healthcare, marketing, and entertainment. As the uses of immersive Virtual Reality (VR) technologies are growing, there is a rapidly increasing need for robust affect recognition in VR settings. However, the integration of affect detection methodologies with VR remains an unmet challenge due to constraints posed by the current VR technologies, such as Head Mounted Displays. This EngD project is designed to overcome some of the challenges by effectively integrating valence and arousal recognition methods in VR technologies and by testing their reliability in seated and room-scale full immersive VR conditions. The aim of this EngD research project is to identify how affective states are elicited in VR and how they can be efficiently measured, without constraining the movement and decreasing the sense of presence in the virtual world. Through a three-years long collaboration with Emteq labs Ltd, a wearable technology company, we assisted in the development of a novel multimodal affect detection system, specifically tailored towards the requirements of VR. This thesis will describe the architecture of the system, the research studies that enabled this development, and the future challenges. The studies conducted, validated the reliability of our proposed system, including the VR stimuli design, data measures and processing pipeline. This work could inform future studies in the field of AC in VR and assist in the development of novel applications and healthcare interventions