About this paper:
Appears in: ICERI2015 Proceedings
Publication year: 2015
Pages: 3650-3654
ISBN: 978-84-608-2657-6
ISSN: 2340-1095
Conference name: 8th International Conference of Education, Research and Innovation
Dates: 18-20 November, 2015
Location: Seville, Spain
The strategies used to educate, can no longer be the same. Our students have their lives full of learning stimuli that we must identify and take advantage of them. We searched the models that teachers use to help students to understand the topics covered in courses, and we discovered some models facilitate the review of concepts with videos, exercises and quizzes but not take advantage of new skills students have. Besides not encourage the creativity in the students, these also do not face the students with challenging activities that they can refine with an automated guidance or advice. Our work is based by this principle.

The LSAT (Learning Supported by Automatic Tool) model has as its primary purpose that students can solve interactive exercises receiving feedback like the teacher were advising, personalized and face to face. Making students feel supported at all times, emphasizing the course topics and motivated towards knowledge, and when the students feel more supported their learning increase substantially.

The LSAT model is based on detects the concepts for each topic to be learned. These concepts are used to design learning networks, which guide students when they are studying a subject. A learning network is a group of exercises with different difficulty levels for each of the concepts that the student must learn. The aim of these exercises is to detect whether the student has learned the subject or which are lacking knowledge or misunderstood to be strengthened. The exercises are organized in levels, which are used to determine the degree of knowledge that the student has about the subject. The most important part of learning networks is the detection of lacking knowledge. For this each exercise is accompanied by three or more solutions. One must be the correct answer, and the others are used as distractors that allow identify what needs to be strengthened. When the student solves an exercise correctly, he goes to the next level. But if the student selects in response a distractor, LSAT provides a capsule explanation-feedback as large as necessary with the intention that students acquire the missing knowledge and lower it to one of the previous levels selected on the concept that was reinforced.

The exercises are arranged to form a knowledge network, on the roads within each network will guide the student to feel satisfied when he finishes his learning in the topic. This sequence of exercises to be solved by the students never follows the same patterns as it depends heavily on prior knowledge and lack of knowledge.

Even today there are many platforms that support the creation of exercises and components but none of them allows students to learn from their own mistakes, neither are dynamic nor flexible. So the model cannot be supported by these platforms. The model must be accompanied by a technology platform, which includes the use of emerging technologies available for all major mobile devices, where the students can get the studies concepts in a creative, agile and direct way.

LSAT encourages in students skills like creative and innovative thinking, problem solving and competences of the profession. It also provides flexibility because it allows students face exercises depending on their ability and knowledge.
LSAT, learning network, tutoring.