{'fraction_non_alphanumeric': 0.011904761904761904, 'fraction_numerical': 0.0, 'mean_word_length': 5.910958904109589, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Methodological Approach to Provide Effective Web-Based Training by Using Collaborative Learning and Social Networks

This paper presents an approach to rebuild the benefits lost from moving from traditional Instructor-led Training to Web-based Training by using Computer-Supported Collaborative Learning and Social Networks. The innovative approach of using Learning Analytics and Educational Data Mining techniques to track and analyse the interactive behavior of on-line collaborative learning and social networks is explored to enhance and improve corporate distance training. The results of this multidisciplinary proposal addressing pedagogical, technological and business issues to support Web-based Training becomes decisive for enhancing and improving the overall distance training experience and for finding new opportunities for cost-effective ways to deliver training programs. We believe the outcomes of this research will be crucial for greatly enhance and improve corporate distance training.