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This paper demonstrates how to use MONTO-machine-readable ontology for teaching word problems in mathematics. MONTO is a combination of various ontologies. After presenting a review of the literature of problem solving and math education, this paper presents a framework that is used for evaluation of the systems available in the literature for teaching problem solving in mathematics. This paper analyzes the existing systems and evaluates them against the framework to state the gaps. It also describes MONTO and demonstrates its use. This paper also discusses how the use of MONTO bridges the gaps found in the literature of tutoring systems used for teaching problem solving. A description of the system implemented using MONTO is included along with the key functionalities of the system derived from the ontology. A discussion of how these functionalities are useful for teaching word problems is included too. This paper also presents the results of a small-scale study conducted to evaluate the functionalities that are derived from the ontology. Introduction and background A student who has been taught mathematical problem solving can be strong in analyzing a large amount of quantitative data, can use mathematics in practical ways, and can be analytical both in thinking for herself and in examining the arguments put