The booming digital-content industry has resulted in an increasing number of e-learning Internet websites that provide online learning services. Recommendations for learning sites are used by diverse learners to identify the most appropriate learning resources. However, research into recommendations about learning has concentrated primarily on suggestions for teaching materials to be used in a particular learning program, and studies have focused on improving the techniques underlying these recommendations without addressing the possibilities for interdisciplinary learning or changes in learner preferences. This study implemented and evaluated a system that recommends interdisciplinary pedagogical resources while recognizing changes in the foci of educational efforts and interests. This system was designed to satisfy individualized learning demands by recommending the most suitable content within an interactive context. Evaluations of learners' attitudes and intentions after using the proposed system revealed widespread acceptance. Data analysis demonstrated that system stability and interface satisfaction were the key factors in learners' attitudes. Indeed, interface satisfaction was the strongest predictor of recommendation accuracy and content satisfaction. (Contains 4 tables and 4 figures.)