心理发展与教育  2016, Vol. 32 Issue (6): 706-716.   PDF    
http://dx.doi.org/10.16187/j.cnki.issn1001-4918.2016.06.09
国家教育部主管、北京师范大学主办。
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文章信息

王翠翠, 徐琴芳, 陶沙 .2016.
WANG Cuicui, XU Qinfang, TAO Sha .2016.
干预-应答模式鉴别学习障碍的有效性及其调节因素:20年研究的元分析
The Validity of the RTI Model for Identifying Learning Disabilities and the Moderators: A Meta-analysis of the Past Two Decades' Studies
心理发展与教育, 32(6): 706-716
Psychological Development and Education, 32(6): 706-716.
http://dx.doi.org/10.16187/j.cnki.issn1001-4918.2016.06.09
干预-应答模式鉴别学习障碍的有效性及其调节因素:20年研究的元分析
王翠翠1, 徐琴芳1,2, 陶沙1     
1. 北京师范大学认知神经科学与学习国家重点实验室, 北京 100875 ;
2. 中国基础教育质量监测协同创新中心, 北京 100875
摘要: 本研究采用元分析方法探讨在学习障碍的鉴别中兴起的干预-应答(Response to Intervention,RTI)模式鉴别学习障碍内部亚组的有效性及其调节因素。通过系统检索1996-2015年的文献,获得了34项研究,包括6127名学生的45个样本、261个效应值。元分析结果表明,RTI模式可有效区分学习障碍风险儿童的内部亚组,对干预无应答和有应答的学生在学业成就、认知技能、行为等多方面存在系统、显著和持久的差异,但仍存在个体应答状态的进一步分化。RTI模式对于学习障碍风险儿童内部变异的区分效果受到干预对象、干预层次、干预时间、应答指标选择、测量方法和切分点等因素的影响。本元分析结果不仅为认识RTI模式鉴别学习障碍的有效性提供了进一步证据,更重要的是通过系列调节效应分析,为合理实施RTI模式鉴别学习障碍提供了直接依据。
关键词: 干预-应答模式    学习障碍鉴别    元分析    
The Validity of the RTI Model for Identifying Learning Disabilities and the Moderators: A Meta-analysis of the Past Two Decades' Studies
WANG Cuicui1, XU Qinfang1,2, TAO Sha1     
1. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875 ;
2. National Innovation Center for Assessment of Basic Education Quality, Beijing 100875
Abstract: Learning disability is one of common neurocognitive developmental disorders among children and adolescents. The mode of Response to intervention (RTI) has been recommended to identify learning disabilities since 2004.However, the validity of the RTI model for identifying learning disabilities has been questioned. This study aimed to exam the validity of the RTI model and the moderating effects of the major variables being involved in the application of RTI model on the basis of the past two decades' of studies. Articles were obtained using keywords, i.e., "RTI(response to intervention) "and "Dyslexia" or "Dyscalculia" or "Specific learning difficulties/disorders" or "Reading disorder (s)/difficulties" or "Mathematical disorder (s)/difficulties" from Web of science, Psychoinform and CNKI. Thirty-four studies published within 1996 to 2015 met the criteria and were included into the meta-analysis, yielding 45 samples (N=6,127) and 261 weighted effect sizes (ESs). Results indicated:(1)The non-responders performed significantly poorer on academic achievement, cognitive skills and behaviors than the responders, and the ESs of all the variables were above 0.5.(2)Evidences from six longitudinal studies indicated that the gap between the groups of responders and non-responders were persistent across time on academic achievement and cognitive skills, but some responders may perform similarly to the non-responders at the follow-up assessments.(3)Moderating effects were found significant for the severity of learning difficulty, intervention tier and duration. Significantly larger ESs emerged from the studies about at-risk students, using short-term intensive Tier 2 intervention rather than from those students with severe learning difficulties, using long-term multi-tiered intervention.(4)Moderating effects were also found significant for measures and criteria of responsive status. Academic achievement rather than cognitive skills were more reliable as the indicators of responsiveness. Compared with the growth or the dual discrepancy criteria, the achievement status was more reliable in differentiating responders and non-responders. When standardized, norm-referenced instruments were used for measuring academic achievement, the 16th percentile would be recommended as the cut-off points. And when non-standardized instruments were used, the 25th percentile would be preferred. Findings from this meta-analysis support the RTI model valid for identifying the subgroups of at risk students for learning disabilities. Guidelines for implementing RTI model in research and practices were recommended. Future directions were also discussed.
Key words: response to intervention (RTI)    identification of learning disability    meta-analysis    
1 引言

学龄儿童学习障碍的发病率高达5%~15%,是儿童青少年期常见的神经发育障碍(Butterworth & Kovas,2013)。准确鉴别是有效预防和干预学习障碍的基础,2013年美国精神疾病诊断和统计手册第五版(DSM-V)推荐使用“干预-应答(Response to Intervention,RTI)”等鉴别模式(DSM-V,2013,pp. 66-70)。RTI模式鉴别学习障碍的基本假设是,个体对有效的干预会出现应答差异,可据此区分低成就学生的不同亚组。在接受有效的干预后,当个体的学业水平和技能回归到正常范围,则定义为“对干预有应答者”;如果个体仍然存在学业成就水平低下和技能缺陷,即为“对干预无应答者”,需要给予长期、系统的特别教育训练(Vellutino et al.,1996; Fuchs,Mock,Morgan,& Young,2003; 刘云英,陶沙,2007)。

然而不少研究者对于RTI模式能不能有效、稳定地鉴别学习障碍提出了质疑。第一,RTI模式中干预标准不统一(Hale et al.,2010),应答指标和标准等也不同,这些可能导致鉴别结果存在差异(Fuchs,Mock,Morgan,& Young,2003; Fuchs,Fuchs,& Prentice,2004; Speece & Walker,2007)。第二,应用RTI费时费力,可能导致学习障碍风险儿童错过最佳个别干预时机(Reynolds & Shaywitz,2009a)。第三,RTI鉴别出的有应答者在回归课堂后可能难以持续进步(Vaughn,Linan-Thompson,& Hickman,2003)。

对此,已有3项元分析探讨了与RTI模式鉴别学习障碍有效性有关的问题(Al Otaiba & Fuchs,2002Burns,Appleton,& Stehouwer,2005Tran,Sanchez,Arellano,& Swanson,2011)。第一项元分析整合了2000年前23项有关读写干预后无应答者特征的研究,发现早期读写干预对存在学习障碍的学生有益,但仍有相当数量的无应答者存在技能缺陷(Al Otaiba & Fuchs,2002)。第二项元分析基于2004年前的21项研究指出运用RTI可能有助于减少学习障碍鉴别的假阳性问题(Burns,Appleton,& Stehouwer,2005)。第三项元分析整合2009年前有关RTI鉴别学习障碍的13项研究,发现前测的技能差异可以解释后测干预应答30%的变异,但并没有发现干预时长、层次、应答标准对鉴别结果的调节效应,可能与样本相对较少有关(Tran et al,2011)。综上,已有元分析初步提示RTI有助于控制学习障碍鉴别的假阳性问题,其鉴别出的无应答者与正常学习者相比存在明显、特定的认知技能缺陷,但是对经由RTI鉴别出的学习障碍高危群体不同亚组间(有应答和无应答者)有何差异、以及亚组差异的稳定性还缺少整合分析,而且需要进一步研究RTI模式的鉴别结果是否受到干预层次、时长、对象、应答标准等因素的影响等问题。

为此,本研究拟通过元分析首先检验RTI模式能否鉴别出具有不同特点的亚组及其时间的稳定性。已有研究表明学习障碍者在相关多项认知技能上存在缺陷,如阅读障碍者存在语音加工缺陷(Melby-Lervåg,Lyster,& Hulme,2012)、语音意识和快速命名的“双重缺陷”(Wolf & Bowers,1999),一般学习障碍者存在工作记忆、言语智力(Scarborough,1998)以及注意力方面的缺陷(Dion,Roux,Landry,Fuchs,Wehby,& Dupéré,2011),因此研究RTI模式鉴别出无应答者的特征可以从学业成就、认知技能和行为表现三个维度进行分析。

由于干预和应答界定是RTI模式实施的关键环节,而现实操作中在这两个环节又存在大量差异,因此,本研究拟进一步系统分析来自干预和应答界定环节的变异可能对RTI鉴别学习障碍有效性产生的调节作用。为此,本研究第二个目的在于探讨RTI模式干预的对象、层次、时长等对RTI模式鉴别学习障碍有效性的影响。在干预对象上,既有以幼儿园和小学低年级儿童为对象的研究,也有以小学高年级学生或中学生为对象的研究;在干预层次方面,干预既可能是从全体(整班)-小组-个别的多层次干预(Fletcher & Vaughn,2009),强度逐步递进,也可能只在某一层次上开展。由于多层级干预时间周期长,可能存在“观望失败”(Watch-them-Fail)、错过最佳高强度干预时机等风险(Reynolds & Shaywitz,2009a),因此,为了提高鉴别效率,不少研究在初次筛选后直接采用第二层的小组干预(Case,Speece,& Molloy,2003; Al Otaiba & Fuchs,2006; Amtmann,Abbott,& Berninger,2008)。那么采用不同层次、不同时长的干预是否会产生不同的学习障碍鉴别结果?

本研究的第三个目的是探讨应答界定的不同操作策略对RTI模式鉴别学习障碍有效性的影响。应答指标、测量方法和应答切分点是应答界定的主要构成成分。在干预应答测量方法上,目前研究主要采用以干预后成就水平为指标的基准线法、以平均成就变化速率为指标的增长差异法,以及两者结合的双重差异法等(Fuchs & Deshler,2007)。在应答与否的切分点选择上,目前研究中存在百分比、固定的基线分值或标准差等不同策略(Compton,2000; Vaughn,Linan-Thompson,& Hickman,2003; O’Connor,Harty,& Fulmer,2005)。

2 研究方法 2.1 文献检索与筛选

本研究将 “干预-应答模式”和“学习障碍”、“阅读障碍”、“计算障碍” 、“数学障碍”作为中文文献搜索的关键词,将“RTI(response to intervention)”and “Dyslexia” or “Dyscalculia” or “Specific learning difficulties/disorders” or “Reading disorder(s)/difficulties” or “Mathematical disorder(s)/ difficulties”作为英文文献搜索的关键词,在“Web of science”、“Psychoinform”、“中国知网”三个数据库中检索出从明确提出RTI观点的 1996年(Vellutino et al.,1996)到2015年12月的608篇相关文献。在此基础上,采用“滚雪球”的方法进一步全面搜索了相关文献。对无法获得全文或信息呈现不全的文献,通过email与文章作者联系获取。由于在中文文献库中没有发现任何有关RTI鉴别学习困难的实证研究,最终进入筛选的文献均为英文文献。进一步文献筛选的标准是:报告了干预后鉴别的结果(包括有、无应答的人数或者比例)或报告了有、无应答者的特征(包括均值、标准差或者效应值)。最终筛选出34篇文献进入元分析(34项文献的基本情况可向作者获取)。

2.2 编码

对检索出的文献进行编码,包括作者名、发表时间、样本人数、年龄或年级、干预领域、对象困难程度、层次、时长、内容、应答指标、测量方法、切分点、无应答人数、效应量、有无追踪。其中阅读障碍的干预研究有30项,参与人数5327名;数学或者数学阅读双重障碍的干预研究有4项,参与人数800名。由于阅读障碍是学习障碍最常见的类型,约占学习障碍总体的80%(Lyon,1995),且RTI对于阅读障碍鉴别的研究也相对丰富,因此本研究收集到的文献主要是阅读障碍,这和阅读障碍在学习障碍中的高比例以及相关研究的高比例一致。

在阅读障碍研究中学业成就指标包括单词认读、假词拼读、流利性、阅读理解,单词拼写、词汇;在数学障碍研究中学业成就指标包括算术和数学综合成绩。认知技能指标包括语音意识、字母知识、快速命名、工作记忆、言语智力、非言语智力等。问题行为和注意力是衡量学生行为表现的两项常见指标。在干预对象的困难程度上,根据困难程度将其分为存在学习障碍风险组和持续困难组。在干预时长上,参照以往研究(National Reading Panel,2000),本研究以中位数34小时区分干预时长,将34~180小时的干预定为长时干预,8~34小时的干预定为短时干预。在切分点上,根据测试的分值和切分标准,我们参照正态分布曲线,将所有的切分点转换成百分位数的形式,其中标准化测试中85分(M=100,SD=15)定义为16%,90分(M=100,SD=15)、0.75SD定义为10%,中位数定义为50%(Fuchs et al.,2003)。

由于有的研究包含多个指标、多组比较,或者存在不同干预层次、干预时长和鉴别指标的比较,因此基于34项研究共获得独立样本45个,效应量261个。所有编码由前两位作者分别独立完成,二者的一致性达到95%。两位作者编码的不一致的地方经过所有作者讨论或咨询原文献作者最终达成一致。

2.3 元分析过程 2.3.1 数据处理

采用元分析软件Comprehensive Meta-analysis 3.0(Borenstein,Hedges,Higgins,& Rothstein,2014; meta-analysis.com),根据均值、标准差和样本个数计算出有、无应答者在学业成就、认知技能和行为表现等各个变量的效应量(Cohen’s d),并根据样本量修正,修正后的Cohen’s d的平均方差是通过对各组的样本方差按样本容量进行加权处理,以控制总体效应值的估计偏差(Ellis,2010)。Cohen’s d ≥0.2为小效应,d ≥0.5为中等效应,d ≥0.8为大效应(Cohen,1988)。由于本元分析是基于不同被试、干预方法的研究,因此我们采用随机效应量模型计算平均效应量,随机效应量=效应量*权重/∑权重,权重=1/组内变异+组间变异(Borenstein,Hedges,Higgins,& Rothstein,2014)。

2.3.2 发表偏差检验

采用漏斗图(Funnel Plot)法与Egger’s 检验方法来评估本元分析涉及研究的发表偏差。漏斗图不对称时可能存在发表偏差。当Egger’s检验的p值大于0.05时,表明没有显著的发表偏差(Rothstein,Sutton,& Borenstein,2006)。本元分析中,大部分研究处于漏斗图的顶部,且相对均匀地分布在平均值的两侧,Egger’s检验表明t(44)=1.42,p=0.16,提示本元分析涉及研究的发表偏差不显著。

2.3.3 异质性检验

使用Q检验来检测效应量异质性是否显著(Hedges & Olkin,1985);使用I2(异质性可以解释总体变异的比例)进一步检测其异质的程度,I2=0%为无异质性,I2=25%为低异质性,I2=50%为中度异质性,I2=75%为高异质性(Borenstein et al.,2014)。异质性显著且程度高则提示有必要进一步进行调节效应分析。本元分析中(表 1),16项结果中有15项异质性达到显著水平,仅在字母知识上异质性检验不显著;I2检验发现14项结果的异质性变异达到了中等程度以上,仅非言语智力的异质性在中等水平以下,因此,有必要对字母知识和非言语智力以外的14项结果进行调节效应分析。

表 1 有、无应答者在学业成就、认知技能和行为表现指标上的效应量分布和异质性检验
结果变量样本效应量SE 95% 置信区间 QI2(%)
下限上限
单词认读311.740.161.432.05 300.55***90.02
假词拼读 211.140.150.851.4290.34***77.86
流利性23 1.95 0.141.682.21112.93***80.52
阅读理解 24 1.690.191.322.07183.78***88.03
拼写8 1.210.360.511.91111.06***93.70
词汇8 1.04 0.260.531.56 59.36***88.21
算术5 1.650.440.78 2.52 56.88***92.97
数学综合5 2.170.401.382.97 28.39**85.91
语音意识20 1.200.200.811.58175.62***89.18
字母知识5 0.620.180.270.98 3.810
快速命名22 0.810.100.621.01 61.95***64.49
工作记忆5 0.560.240.081.03 23.24***82.79
言语智力22 0.660.100.470.84 52.98***60.37
非言语智力 16 0.570.080.420.72 24.92*39.8
问题行为6 0.500.240.241.1912.23*59.09
注意9 0.66 0.140.38 0.9527.07**70.45
3 研究结果 3.1 RTI模式鉴别学习障碍有效性检验

首先,从整体上看,结果一致性地表明,干预后有无应答者在学业成就、认知技能和行为表现上差异的效应量均在中等程度以上(Cohen’s d ≥ 0.5,见表 1)。可见,无论在阅读还是数学障碍上、采用何种指标,RTI模式鉴别出的有无应答者在学业成就、认知技能、行为表现上均存在显著的差异。从表 1中可以看出,阅读障碍风险人群中有无应答者之间语音意识和快速命名上差异的效应量均在0.8以上,说明二者在这两项认知技能上存在明显的差异,符合已有研究提出的阅读障碍“语音意识-快速命名双重缺陷”假设(Wolf & Bowers,1999)。4项有关数学障碍或数学阅读双重障碍的研究一致发现有、无应答者在言语和非言语智力、工作记忆、注意和问题行为上的差异效应量中等及以上。上述结果表明RTI模式对鉴别学习障碍亚组有效。同时,根据效应量推测两组分布的分离程度(Cohen,1988)可知干预后有、无应答者仅在数学综合一个指标上的分离达到80%以上,而在其他指标上普遍存在接近50%以及更大比例重合的可能。可见,学习障碍的困难表现不是全或无,而的确存在一定程度的连续变化特征(Fletcher,Francis,Morris,& Lyon,2005; Shaywitz,1998)。

其次,34项研究中有6项研究报告了追踪的数据结果,均为阅读障碍研究,追踪时间范围为5个月-3年,涉及单词认读、假词拼读、流利性、阅读理解、语音意识五个指标,共计独立样本14个,效应量总数63个。在组平均水平上,在干预后、1年内、2年内RTI模式鉴别出的有无应答者在多项指标上差异的效应量都大于1(见表 2),说明RTI模式鉴别出的有无应答者在学业成就、认知技能上差异稳定存在。此外,有两项研究报告了在撤除干预后,RTI模式鉴别出的有无应答者在发展过程中存在内部重新分化的现象(Scheltinga,van der Leij,& Struiksma,2010; Vaughn et al.,2003)。有关数学学习障碍的相关研究没有长期追踪,其干预应答分类的稳定性尚需进一步研究。

表 2 有、无应答者在学业成就、认知技能指标上差异稳定性随机效应量分布表
指标样本效应量SE 95% 置信区间
下限上限
干预后
单词认读41.890.281.342.44
假词拼读21.140.320.521.76
流利性32.180.321.542.81
阅读理解31.530.111.321.75
语音意识31.350.310.741.96
一年后
单词识别41.590.400.802.39
假词拼读21.440.250.961.93
流利性31.760.440.902.62
阅读理解31.340.280.891.88
语音意识21.310.131.061.56
两年后
单词识别32.230.551.163.30
假词拼读12.020.301.442.61
流利性21.780.670.463.14
阅读理解21.250.470.342.17
语音意识11.310.131.061.56
3.2 干预对象的困难程度、干预层次和时长对RTI模式鉴别有效性结果的调节作用分析

干预对象的困难程度对有、无应答者单词认读、阅读理解、拼写的差异有显著调节效应(Q(1)=8.9,p=0.001; Q(1)=27.06,p=0.001; Q(1)=5.61,p=0.02),对认知技能和行为表现差异的调节效应不显著(见表 3)。存在学习障碍风险组学生中有、无应答者干预后差异平均效应量稳定地保持在1以上。因此,RTI相对更加适合对存在学习障碍风险学生的亚类型鉴别。

表 3 干预对象的困难程度对学业成就的调节效应随机模型分析
结果变量调节变量 同质性分析类别名称样本效应量SE 95%置信区间双尾检验
Q组间dfp下限上限Zp
单词认读干预对象8.910.001风险241.960.171.612.311.240.00
持续困难70.960.280.411.523.410.00
阅读理解干预对象27.0610.001风险211.940.191.562.3110.150.00
持续困难30.30.25-0.190.791.20.23
拼写干预对象5.6110.02风险61.490.420.672.313.580.00
持续困难20.280.3-0.30.860.940.35

干预层次对有、无应答者单词认读、词汇、流利性上的差异有显著的调节效应(Q(1)=5.11,p=0.024;Q(1)=7.56,p=0.006;Q(1)=3.92,p=0.05)(见表 4)。总体而言,T2层次干预后鉴别出的有、无应答者学业成就差异的效应量明显较高。

表 4 干预层次对学业成就的调节效应随机模型分析
结果变量调节变量 同质性分析类别名称样本效应量SE 95%置信区间双尾检验
Q组间dfp下限上限Zp
单词认读干预层次5.1110.024其他层次61.20.230.761.645.290.00
T2181.950.241.482.428.090.00
词汇干预层次7.5610.006其他层次20.310.150.010.622.010.04
T261.310.330.671.963.980.00
流利性干预层次3.9210.05其他层次71.570.231.112.026.760.00
T2162.120.161.812.4313.50.00

干预时长对有、无应答者阅读理解、词汇、拼写差异有显著调节效应(Q(1)=8.56,p<0.001;Q(1)=7.56,p=0.01;Q(1)=5.61,p=0.02)(见表 5)。但是,即使在干预时长调节作用显著的变量上,干预时间延长并没有显著提高鉴别效益,短时干预也能有效区分有、无应答者。

表 5 干预时长对学业成就的调节效应随机模型分析
结果变量调节变量 同质性分析类别名称样本效应量SE 95%置信区间双尾检验
Q组间dfp下限上限Zp
阅读理解干预时长8.5610.00132.220.231.772.689.610.00
111.140.290.581.713.990.00
词汇干预时长7.5610.0161.310.330.671.963.980.00
20.310.150.010.622.010.04
拼写干预时长5.6110.0261.490.420.672.313.580.00
20.280.3-0.30.860.940.35
3.3 鉴别标准对RTI模式鉴别有效性结果的调节作用分析

我们首先考察应答指标选择的调节作用。数学障碍研究主要采用算术或数学加阅读的双指标,这可能是由于阅读与数学障碍有一定共发(Fuchs,Fuchs,& Compton,2013)。阅读障碍研究中多以流利性、单词解码能力、阅读理解为指标,单一指标的使用远远多于双指标使用;流利性和单词解码相对最常见,使用阅读理解指标的研究最少,这与已有阅读障碍研究多集中于单词水平有关。应答指标选择显著调节了单词认读、阅读理解、流利性、拼写差异(Q(1)=16.96,p<0.001; Q(1)=60.33,p<0.001; Q(1)=20.35,p<0.001;Q(1)=13.03,p<0.001),以及问题行为差异(Q(1)=5.11, p=0.02)(见表 6)。

表 6 应答指标对学业成就和行为表现的调节效应随机模型分析
结果变量调节变量 同质性分析类别名称样本效应量SE 95%置信区间双尾检验
Q组间dfp下限上限Zp
单词认读应答指标16.96 20.00 流利性101.50 0.24 1.03 1.96 6.27 0.00
流利性+单词解码23.35 0.39 2.59 4.12 8.61 0.00
单词解码71.85 0.25 1.37 2.33 7.52 0.00
阅读理解应答指标60.33 30.00 阅读理解1 3.54 0.29 2.97 4.11 12.16 0.00
流利性11 1.35 0.20 0.97 1.74 6.84 0.00
流利性+单词解码2 3.02 0.20 2.62 3.42 14.88 0.00
单词解码3 1.88 0.17 1.55 2.21 11.16 0.00
流利性应答指标20.35 30.00 阅读理解1 1.43 0.21 1.01 1.85 6.70 0.00
流利性13 1.84 0.13 1.58 2.10 13.96 0.00
流利性+单词解码2 2.97 0.47 2.04 3.89 6.29 0.00
单词解码1 2.75 0.27 2.23 3.27 10.28 0.00
拼写应答指标13.03 20.00 流利性40.42 0.32 -0.21 1.05 1.31 0.19
流利性+单词解码21.96 0.31 1.35 2.57 6.29 0.00
单词解码22.02 0.70 0.65 3.40 2.89 0.00
问题行为应答指标5.11 10.02 流利性50.92 0.28 0.37 1.46 3.31 0.00
阅读理解10.09 0.24 -0.38 0.56 0.37 0.71

在阅读障碍研究中,使用单词解码和流利性的双重指标筛选出的有、无应答者差异的效应量均显著较高,这和两项直接对比单一指标和双重指标的研究结果一致(Barth et al.,2010; Fletcher et al.,2011)。另一方面,在早期(幼儿园-小学3年级)阅读风险筛选研究中,有30个样本采用了单词解码或流利性为应答指标,区分出的有、无应答者差异显著,提示对低年级的阅读风险儿童而言,单词解码能力和流利性是鉴别应答的良好指标;随着阅读能力的发展,在高年级的阅读障碍研究中包括阅读理解能力的综合性指标更适合作为应答指标(Denton,Wexler,Vaughn,& Bryan,2008; Frijters,Lovett,Steinbach,Wolf,Sevcik,& Morris,2011)。可见,应答指标的选择和鉴别对象的阅读经验与能力有关。

其次,测量方法显著调节了单词认读、流利性、词汇差异(Q(1)=22.99,p<0.001; Q(1)=9,p=0.01; Q(1)=5.51,p=0.02),以及语音意识差异(Q(1)=5.54,p=0.02)(见表 7)。总体而言,相较于增长法和双重差异法,使用干预后的平均成就水平作为测量方法鉴别出的有、无应答者差异的效应量普遍较高。在本元分析中,有37个样本选择以干预后的成就水平为测量依据,7个样本采用增长法或增长和水平均不达标的双重差异法,可见已有研究多倾向于采用干预后的成就水平作为测量方法。

表 7 测量方法对学业成就和认知技能的调节效应随机模型分析
结果变量调节变量 同质性分析类别名称样本效应量SE 95%置信区间双尾检验
Q组间dfp下限上限Zp
单词认读测量方法22.9920.00双重差异41.020.110.811.239.580.00
增长法31.760.161.452.0810.980.00
成就水平241.850.191.472.239.520.00
流利性测量方法9.0020.01双重差异11.540.121.301.7812.610.00
增长法31.420.151.121.739.200.00
成就水平192.040.161.732.3512.820.00
词汇测量方法5.5110.02增长法20.400.150.110.682.730.01
成就水平61.290.350.601.973.680.00
语音意识测量方法5.5410.02双重差异10.360.31-0.26 0.971.130.00
成就水平181.250.210.831.665.910.00

第三,在干预应答的切分点上,其调节效应表现在词汇(Q(1)=6.06,p=0.05)、语音意识(Q(1)=105.39,p<0.001)、快速命名(Q(1)=20.48,p<0.001)、以及注意上(Q(1)=23.54,p<0.001)(见表 8)。切分点选择依赖于所采用的测量方法。在增长测量中,采用中位数50%为切分点鉴别出的有、无应答者差异的效应量较低。在基线水平测量中,在缺乏标准化测试时,以参照组后25%作为切分点时不同变量上的效应量变异较大。在采用标准化测试时,以16%为切分点鉴别出的有、无应答者之间不仅差异明显,而且较为稳定,但是有些样本仅有1项,限制了统计分析。总体而言,在标准化测试中采用16%为切分点较为稳定,在非标准化测试中,采用参照组25%为切分点可以作为一种便利选择。

表 8 切分点对学业成就、认知技能和行为表现的调节效应随机模型分析
结果变量调节变量 同质性分析类别名称样本效应量SE 95%置信区间双尾检验
Q组间dfp下限上限Zp
词汇切分点6.0620.0516%51.470.410.672.273.590.00
25%20.470.200.080.852.360.02
50%10.360.20-0.040.761.770.08
语音意识切分点105.3930.0010%11.140.350.451.843.220.00
16%13.080.212.663.5014.480.00
25%121.380.200.981.786.780.00
50%50.450.140.170.733.120.00
快速命名切分点20.4840.0010%10.880.350.201.552.530.01
16%20.680.160.370.984.300.00
25%110.740.140.451.025.100.00
33%10.710.210.301.123.360.00
50%60.830.120.601.076.890.00
注意切分点23.5420.0016%41.040.120.801.288.640.00
25%40.250.110.030.462.250.02
50%10.640.210.241.043.110.00
4 讨论

本研究检验了1996年到2015年20年间34项RTI模式鉴别学习障碍有效性的研究,结果支持RTI模式是鉴别学习障碍风险学生不同亚组的有效方法,其鉴别出的亚组差异受到干预对象的困难程度、干预层次和时长、应答指标、测量方法、切分点的调节。元分析结果表明,RTI模式相对更适合于区分学习障碍风险儿童的亚组;短时间的第二层次干预具有较高的鉴别效率。以学业成就作为应答指标、干预后的平均成就水平为测量方法是评价干预应答最常使用和有效的方法,干预应答的切分点选择受到测量工具的标准化影响。

4.1 RTI模式是鉴别学习障碍亚组的有效模式

RTI模式的基本假设是根据学生对科学验证有效干预的应答情况,可区分“由教育经验不足带来的学习障碍”和“由缺陷导致的学习障碍”等不同亚组(Vellutino et al,1996)。本研究显示,尽管不同研究针对不同对象、领域,采用了不同的干预方法、鉴别指标,但其鉴别出的无应答者都相对一致地表现出学业成就、认知技能、行为表现的显著缺陷,支持对干预无应答者具有显著成就、技能、行为缺陷,可能是 “由缺陷导致的学习障碍”。

另一方面,RTI模式鉴别出的有应答者在学业成就、认知技能等方面在干预后不仅显著优于无应答者,而且回归到学业成就和技能发展的正常范围内,显示出的确有部分学业成就低下者的学习困难问题可以通过有效的干预得以缓解和矫正,其学习问题的确可能由于受到教育或经验不充分的影响。但是,RTI模式鉴别出的有应答者是否完全不存在“真正的学习障碍”呢?对这个问题,已有研究并不能给予肯定的回答。一方面,由于追踪研究数量相当有限,因此对这个问题的回答需要基于更多追踪研究的结果。另一方面,现有的少数研究清晰地显示部分应答者在干预撤除后又存在进一步个体分化现象(Scheltinga,van der Leij,& Struiksma,2010; Vaughn et al.,2003)。如何有效预测应答群体中的个体分化值得研究进一步考察。

本元分析结果在一定程度上澄清了人们对于RTI模式操作方法不同可能影响鉴别结果的质疑(Reynolds & Shaywitz,2009b)。在学业成就、认知技能和行为的各项指标上,领域(阅读、数学)并不存在显著的调节作用;在干预对象的困难程度、干预层次和时长、应答指标和标准上,存在一定调节作用。尽管在不同研究中RTI的做法各异,但是都能有效鉴别出有、无应答者。可见,至少在目前积累的证据下,并没有出现人们担心的由于RTI模式操作策略不同所导致的在鉴别学习障碍亚组时存在有效性不足的“必然缺陷”。

4.2 应用RTI模式鉴别学习障碍亚组的操作策略建议

元分析结果表明,干预对象、层次和时长均对RTI鉴别学习障碍有效性的结果产生调节作用。相较于持续困难者,RTI模式更加适合于学习障碍风险儿童的鉴别。对学习障碍的识别越早,干预和鉴别越早,效果就越好(Greenwood,2008Johnson,Mellard,Fuchs & McKnight,2006)。RTI兴起重要原因之一在于将干预和诊断有机结合,能实现早期干预,减少在出现明显问题后才予以鉴别的“亡羊补牢”问题(刘云英,陶沙,2007)。因此当前关于RTI的研究对象多集中于幼儿园和小学低年级阶段。本研究显示,采用较短时间的第二层次小组干预对于鉴别有无应答者已经具有良好效力,长时间、多层次的干预并没有显著增进鉴别效益。因此在RTI的应用中并不必须采用全层次干预,而可以考虑第二层次小组的短时干预,以有助于节省时间,提高鉴别效率。

应答指标、测量方法和切分点选择同样对RTI模式鉴别学习障碍有效性具有一定调节作用。学业成就是鉴别学习障碍的重要应答指标,具有较高的信效度(Fletcher,Francis,Morris,& Lyon,2005),而且采用双重指标差异指标的效果较好,因此在未来的应用中,可以采用学业成就中的双重指标作为应答指标。另外,在测量方法上,双重差异法、增长差异法并没有带来方法上的优势,因此采用干预后成就水平为测量方法较为便利。在切分点的选择上,先前研究限于样本数量未能发现切分点对干预后鉴别结果有调节作用(Tran et al.,2011),而本研究以较多的样本进一步区分测试类型后,发现在标准化测试中采用16%作为切分点比较稳定,而在非标准化测试中以参照组25%作为切分点是较好的选择。

4.3 不足与未来研究方向

本元分析存在以下不足:(1)调节作用检验仍然存在样本量较少且分配不均衡的问题。样本量较少的确是元分析调节效应研究中普遍存在的问题(如Tran et al.,2011; Lundahl,Risser,Lovejoy,2006; Ito,Miller & Pollock,1996; Springer,Stanne,Donovan,1999)。就本研究考察的调节效应而言,有限数量样本结果比较清晰、一致(见表 3-8),但仍然有待在积累更多研究证据的基础上进一步对当前的研究结果进行验证。(2)阅读障碍的研究数量在本研究中为数最多,有待数学障碍等领域研究的进一步推进来检验当前的研究结果。虽然当前结果表明不同领域RTI 模式鉴别学习障碍亚组的有效性相似,但仍然需要后续研究在学习障碍的其他领域中进一步验证。(3)关于有无应答者在干预撤除后重新分化的追踪研究较少,期待未来更多追踪研究提供有、无应答者长期发展变化的更丰富信息。(4)我国关于学习障碍的诊断和干预研究还相当有限,缺乏学习障碍的诊断标准和相应工具,更缺乏基于科学实证检验的干预方案,期待我国研究者在不断积累学习障碍评价工具和干预方案的基础上进一步开展运用RTI模式的学习障碍研究。

5 结论

本研究为认识RTI模式鉴别学习障碍的有效性以及实施RTI模式提供了证据和启示。RTI模式可有效区分学业成就落后儿童的内部变异。对科学验证的有效干预无应答和有应答的学生在学业成就、相关认知技能、行为等多方面存在系统、显著和持久的差异。对干预无应答学生在学业成就与相关认知技能上存在持续、稳定的缺陷。

基于系统的调节作用分析,本研究发现RTI模式更适于对存在学习障碍风险儿童进行亚组的鉴别;采用第二层次小组、较短时间的干预可提高鉴别效率。在应答指标、测量方法、切分点的选择上通常以学业成就作为应答指标,干预后的成就水平为测量方法,切分点的选择依赖是否选用标准化的工具。

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