四、评价与展望
经过四十多年的发展，深度学习已成为国内外教育领域研究的热点与重点，并取得了诸多成果。在这一发展过程中，深度学习的内涵不断扩大。与此同时，深度学习也从理论研究走向实践探索，从宏观走向“宏”“微”并重，且越来越注重实证研究和深度学习的评价研究。未来，深度学习研究应从以下几个方面继续深入发展。
首先，深度学习的实证研究。在深度学习的研究上，国外已进行了诸多实证研究，如通过实证研究探析深度学习的影响因素、形成过程、应用价值等，但为给教育和课堂教学改革提供强有力的证据支撑，这方面的研究还有待进一步挖掘和深入。
其次，深度学习的评价研究。深度学习评价是深度学习研究的重要内容，也是判断学习者是否进行深度学习的重要途径和手段。尽管深度学习是一种涉及认知、情感、人际等多个方面的高阶能力，但现有评价研究大多集中在认知层面，对其他方面关注不够，因而如何构建一个全面、科学的深度学习评价体系将是下一步研究的重点，从而为有效评价深度学习提供依据。此外，尽管传统的问卷调查、纸笔测验等实施方便、评价效率高，但由于深度学习的复杂性、多维性与真实性，这类评价往往难以全面反映深度学习的面貌和特征。所以，如何有效地评价学习者在这些方面的高阶能力亟待解决。就此而言，我们认为强调基于表演、操作、行动等真实表现进行评价的表现性评价可能是深度学习评价研究的一大趋势。例如，SDL项目已采用表现性评价对认知、人际和个人领域的深度学习进行评价。美国斯坦福评价、学习与公平中心（Stanford Center for Assessment, Learning and Equity，简称SCALE）也于2014年开展了指向深度学习的表现性评价项目(91)。
再次，技术支持下的深度学习研究。进入21世纪后，尤其是2010年以来，国内外研究者都非常重视信息技术支持下的深度学习研究，利用信息技术促进深度学习，如王等人探讨了如何在计算机环境中使用认知地图促进复杂问题的深度学习，(92)佩格勒姆等人通过实证研究探讨了播客能否促进深度学习。(93)但是，如何实现信息技术与深度学习的深度融合、如何对技术支持下的深度学习进行测量和评价等问题还有待进一步挖掘和研究。
最后，深度学习的应用与效果研究。自2010年起，以美国、加拿大为代表的国家纷纷把深度学习引入真实的课堂教学场域，验证深度学习的效果，这不但促进了深度学习理论与实践的融合，而且还极大地推动了深度学习的实践研究。但从全球范围来看，这类研究还较为缺乏。未来，应基于相关研究成果构建理论框架和实践模型，进行大规模的深度学习实验项目，在验证和丰富深度学习基本理论的同时，进一步明晰深度学习的实践理路，为课堂教学的深层次变革提供参考和指导。
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